q: On the assembled instrument-product table, exhibit the covariate-balance table of every design control across cost terciles (standardized mean differences pre- and post-entropy-balancing-weights) and the common-support survivor count, and state specifically whether a flagship-class radiometer has any in-support low-cost comparator of comparable retrieval difficulty and technology epoch. Without it, the concavity estimate is extrapolation across incomparable missions, not an interpolated frontier.

facet: identification

raised_by: abadie

priority: high

query_terms: entropy balancing covariate balance standardized mean difference cost strata

query_terms: common support trimming convex hull synthetic control

query_terms: instrument cost balance diagnostic flagship radiometer comparator

status: open


q: Run the within-cell placebo: does the concave cost term survive inside retrieval-difficulty-by-epoch matched cells where cost varies but the geophysical variable does not, or only in the pooled cross-section? Add the fake-cost-shock placebo that assigns a spurious cost difference driven by a known non-accuracy factor (calibration-subsystem choice, build-site or contractor change) currently treated only as measurement error to drop.

facet: empirics

query_terms: within-cell placebo conditional independence cost effect

query_terms: fake cost shock placebo non-accuracy driver

query_terms: coarsened exact matching difficulty epoch cell


q: Give the design-based permutation distribution of the over-specification channel-count edge itself (not just aggregate curvature) under leave-one-instrument-out and randomized cost-ordering reassignment, and report where the claimed edge sits in that placebo distribution. If dropping one expensive instrument moves the edge materially or the edge is not in the tail, the stopping rule is indistinguishable from noise.

query_terms: permutation placebo inference small-N synthetic control edge

query_terms: leave-one-out influential point frontier curvature

query_terms: randomized cost ordering reassignment placebo distribution

status: partial


q: Produce the cost-by-vintage scatter, report the correlation between log development cost and launch year (or NICM normalization epoch), and identify the common-support band in the cost-by-vintage plane where instruments span a wide cost range. If that band is empty or thin, g(cost) is not separable from a secular time trend.

query_terms: cost vintage collinearity launch year common support

query_terms: log development cost launch year correlation radiometer

query_terms: embodied disembodied technical change separability time trend


q: Re-estimate the partially linear model and the second-derivative concavity test inside narrow launch-year (or reprocessing-generation) bands where vintage is fixed, and pre-state the cell-level result that would falsify H1 (e.g. g'' not reliably negative inside any within-vintage band of >= k instruments). If concavity exists only across vintage cells and vanishes within them, the frontier is a secular technology trend relabeled as diminishing returns.

query_terms: within-vintage-band placebo concavity falsification threshold

query_terms: reprocessing generation band g'' second derivative

query_terms: secular technology trend diminishing returns artifact


q: Use the instrument-family time series as its own counterfactual: for at least two sensor lineages (MODIS to VIIRS, the AMSR microwave-radiometer line, an operational sounder series) show the within-family per-generation cost and accuracy trajectories and explain how the estimand distinguishes the within-family effect from the pooled cross-instrument fit. If accuracy rises while cost falls within a lineage, cross-sectional concavity is a between-lineage vintage artifact.

facet: rival

query_terms: within-lineage counterfactual MODIS VIIRS AMSR sounder cost accuracy trajectory

query_terms: sensor lineage donor pool secular trend netting

query_terms: between-lineage vintage heterogeneity returns to cost


q: Does an incident-by-incident audit trail from raw validation record (AOD expected-error vs AERONET, SST bias-and-sd vs in-situ, SMAP ubRMSE vs core sites) to the requirement-normalized accuracy number exist, and does 'fraction of stated requirement met' carry the same operational meaning across all communities, or does requirement-normalization flatten the cross-community variation the frontier must ride on?

facet: measurement

query_terms: requirement-normalized accuracy audit trail cal/val incident

query_terms: fraction of requirement met cross-community equivalence construct

query_terms: AERONET expected error SST bias SMAP ubRMSE normalization


q: State the saturation warrant in grounded-theory terms: at which instrument-product row did new instruments stop yielding new properties of the cost-accuracy relationship, what was the last new property the marginal instrument contributed, and name in advance a class of instrument absent from the frozen table whose addition would change the fitted frontier. Absent a documented stabilization row, the over-specification edge cannot be distinguished from the edge of a convenience sample.

query_terms: theoretical sampling saturation stabilization row constant comparison

query_terms: convenience sample availability intersection frozen table

query_terms: saturation falsifiable prediction unobserved instrument


q: Run the family-by-family stratified comparison: re-estimate curvature and the channel-count edge within each geophysical-variable family (aerosol, SST, soil moisture, precipitation, sounding) separately and show whether one concave story recurs (licensing a formal cross-family claim) or each family yields a different relationship in kind (so the pooled frontier is a forced aggregate). Grounded theory requires a formal claim be earned by cross-substantive-area comparison.

query_terms: family-stratified frontier curvature channel-count edge geophysical variable

query_terms: substantive vs formal theory aggregation artifact one frontier several

query_terms: pooled concavity NICM-E class structure heterogeneity


q: Run the constant-comparative step on the raw validated-accuracy incidents before any regression: show row by row the chain from the original validation statement to the single requirement-normalized number, and demonstrate that 'fraction of requirement met' denotes the same analytic property across families rather than four differently-defined constructs forced under one label. Where does normalization stop comparing like incidents and start imposing equivalence?

query_terms: constant comparative method validation incident raw to normalized

query_terms: imposed equivalence heterogeneous cal/val constructs forcing

query_terms: requirement denominator different community reference standard error model


q: Compute the mechanistic channel-saturation point from a published forward model and radiometric error budget (averaging-kernel / degrees-of-freedom-for-signal calculation) for at least one product family (MODIS aerosol or an IR sounder), compare it head-to-head against the channel count the semiparametric smoother flags as redundant, and pre-register which number is trusted if they disagree. The forward-model DFS number is the independent verifier; the fitted second derivative is a learned surrogate.

facet: mechanism

raised_by: hassabis

query_terms: degrees of freedom for signal averaging kernel channel saturation forward model

query_terms: MODIS aerosol channel set information content head-to-head regression

query_terms: pre-register physics verifier over fitted second derivative


q: Run a power/simulation study on the actual support and effective degrees of freedom showing the cross-validated-beats-null plus reliably-negative-second-derivative test can detect a true concave frontier of the magnitude H1 posits and reject a flat one at dozens of instrument-product rows clustered within dozens of instruments. If it cannot distinguish them, the verifier is untrustworthy and the contribution is unfalsifiable in practice.

query_terms: power simulation shape-restricted concavity test small sample clustered

query_terms: effective degrees of freedom detect concave reject linear

query_terms: inference shape-restricted regression splines multiscale qualitative hypothesis


q: Name in advance one product family where a forward-model information-content analysis predicts the regression will NOT find a concave channel-redundancy edge because calibration drift or geolocation, not channel redundancy, is the binding accuracy limit (e.g. thermal-IR SST/LST), and show the fitted g(cost) reproduces that exception rather than smearing one concavity across heterogeneous physics.

query_terms: thermal infrared SST LST calibration limited not channel redundancy

query_terms: forward model information content negative case exception

query_terms: per-family interacted estimate calibration drift geolocation binding limit


q: Build a head-to-head technology-vs-redundancy discriminator for one product family: hold the physical channel set fixed and tabulate validated-accuracy gains across reprocessing/algorithm-version generations (pure vintage delta) versus accuracy gains from adding channels at fixed vintage, citing the published detector-noise/calibration-stability trend grounding the vintage arm. Until that two-arm table exists, can concavity be distinguished from a disembodied technology-curve artifact at all?

query_terms: fixed channel set reprocessing generation accuracy gain vintage delta

query_terms: embodied vs disembodied technological progress channel redundancy discriminator

query_terms: CrIS noise AIRS radiance uncertainty detector stability trend


q: Compute the forward-model degrees-of-freedom-for-signal saturation curve from NTRS channel center-wavelengths and bandpasses independently and PRE-REGISTER it as the verifier, so the fitted regression over-specification edge is confirmed only when it coincides with the physics-based information-gain-flat channel count. State which is trusted on divergence and what divergence reveals about whether the regression reads redundancy or the technology curve.

query_terms: NTRS channel center wavelength bandpass DFS information content curve

query_terms: pre-registered forward-model verifier regression edge coincidence

query_terms: hyperspectral information content spectrometer design dependence


q: After regressing out epoch, partition supported rows into a within-vintage-band slice where cost varies but technology generation is held constant; report how much cost variance survives inside common support after epoch and difficulty are absorbed, and re-estimate g(cost) on that slice. Is the residual within-vintage cost spread even large enough to fit a flexible concave term, and does concavity survive or collapse once vintage is held fixed?

query_terms: within-vintage slice residual cost variance epoch difficulty absorbed

query_terms: re-estimate g(cost) vintage held fixed concavity survive collapse

query_terms: embodied effort vs technological progress channel redundancy


q: Partition the assembled dataset by geophysical-variable family and re-estimate the marginal-channel-contribution function within each, showing whether the over-specification channel-count thresholds coincide across families. If they diverge, concede the single portfolio-level stopping rule is an aggregate that misprices every individual mission it would descope (Hayek knowledge problem).

raised_by: hayek

query_terms: per-family marginal channel contribution over-specification threshold coincide

query_terms: portfolio stopping rule aggregate misprice individual mission

query_terms: dispersed local knowledge difficulty index within-family gradient


q: By leave-one-instrument-out cross-validation, demonstrate what the fitted concave frontier and over-specification edge predict for the most spectrally elaborate (hyperspectral / novel-band) instruments, and report whether the frontier systematically mislabels high-channel instruments that delivered novel validated products as over-specified. Where does the discovery-suppression burden fall?

query_terms: leave-one-out prediction hyperspectral novel-band instrument over-specified

query_terms: discovery suppression backward-looking population frontier mislabel

query_terms: novel validated product channel set not contemplated at design


q: Quantify residual selection: regress retrieval-difficulty and design controls on cost to report how much cost variance remains unexplained inside common support, then run an Oster-style or Rosenbaum-style bound showing how strong an unobserved mission-judgment / difficulty-cost correlation would have to be to overturn the negative second derivative of g(cost). If a confounder comparable to the difficulty control suffices, the frontier is an artifact, and the headline must be a bound, not a verdict.

query_terms: Oster bound Rosenbaum sensitivity unobserved confounding flip concavity

query_terms: residual cost variance unexplained difficulty controls common support

query_terms: E-value selection on unobservables second derivative sign


q: Report the cross-mission dispersion of per-channel marginal validated-accuracy within common support and show the variance of the mission-specific over-specification optimum around the pooled estimate is small relative to the cost stakes a cap imposes, so a pooled central edge tracks the mission-specific optimum better than the design team's own local knowledge. The channel-selection literature shows the optimal subset is regime/instrument dependent, which cuts against a stable pooled edge.

query_terms: cross-mission dispersion per-channel marginal accuracy pooled edge variance

query_terms: regime instrument dependent optimal channel subset stability

query_terms: mission-specific optimum versus population frontier cost stakes


q: Partition instrument-product rows by whether a channel set was later exploited for a retrieval not contemplated at design time, and test whether channels the model flags as over-specified disproportionately overlap channels that later yielded new validated products. If over-specified-at-build channels are the seedbed of subsequent discovery, the welfare claim must net the foregone-discovery cost.

query_terms: over-specified channel later exploited new validated product overlap

query_terms: foregone discovery cost welfare net seedbed unanticipated retrieval

query_terms: post-launch product line sounder GeoHIS applications developed later


q: Report the partially-linear estimator's output as a decentralized per-channel marginal-validated-accuracy-per-dollar curve with a confidence band (a local shadow price teams price against) rather than a single population edge, and demonstrate whether the local-derivative form is more out-of-sample-robust than a global threshold that, by the candidate's own leave-one-out exposure, extrapolates onto the most spectrally elaborate, data-thinnest instruments.

priority: normal

query_terms: per-channel marginal accuracy per dollar shadow price local derivative

query_terms: out-of-sample robustness local signal vs global population threshold

query_terms: optimal estimation averaging kernel marginal information local state


q: Add a contracting-regime fixed effect (cost-plus vs fixed-price vs partner-furnished) and a building-center fixed effect and report whether the curvature of g(cost) survives, since both regimes coexist in every mission epoch and the epoch dummy cannot separate them. NASA's separate NICM-E CER for Class C / university-led instruments shows the regime moves cost orthogonally to epoch.

raised_by: north

query_terms: contracting regime fixed effect cost-plus fixed-price building center curvature

query_terms: NICM-E Explorer-like Class C institutional regime within epoch

query_terms: procurement regime confound cost discipline versus physics


q: Construct from NTRS lineage and instrument-version records a measured heritage-reuse variable (clean-sheet, modified-heritage, rebuild) and show the over-specification edge is not an artifact of heritage clustering at the low-cost end. NICM-E names significant inheritance as a defining cost characteristic, and instrument-electronics costs diverge from heritage predictions.

query_terms: heritage reuse clean-sheet modified-heritage rebuild coding NTRS lineage

query_terms: heritage clustering low-cost end over-specification edge artifact

query_terms: NICM-E inheritance cost driver instrument electronics divergence


q: Run the direct validating regression of validated accuracy on the component of cost orthogonal to channels-swath-resolution-calibration-mass-power, and report whether that purified residual carries the accuracy signal, since the 'cost as near-sufficient hedonic index of embodied effort' premise is untested and load-bearing. NICM is probabilistic, so design attributes leave residual cost dispersion by construction.

query_terms: validated accuracy on orthogonalized cost residual embodied effort hedonic

query_terms: cost near-sufficient statistic quality residual dispersion test

query_terms: NICM probabilistic CER joint confidence level residual


q: Does the reliably-negative second derivative of g(cost) survive once a coarse mission-epoch dummy is replaced by a continuous launch/formulation-year trend, and are the cheap-and-accurate rows simply the late rows? Report the rank correlation of deflated instrument cost vs launch year within common support, grounded in the investment-specific technical-change identification problem.

query_terms: continuous launch year trend replace epoch dummy second derivative survive

query_terms: deflated cost launch year rank correlation common support late rows

query_terms: investment-specific technological change embodied disembodied separation


q: Does the flat high-cost region reflect hardware capability (embodied vintage) or the accuracy lift of the latest reprocessing collection (disembodied vintage)? Recover the per-accuracy-row DAAC collection/version stamp and ATBD algorithm-baseline date that date the accuracy number independently of the build, and decompose the flat region into embodied vs disembodied vintage.

query_terms: DAAC collection version stamp reprocessing date accuracy independent of build

query_terms: embodied versus disembodied vintage flat high-cost region decompose

query_terms: MODIS Collection 6 MAIAC Deep Blue AERONET V3 reprocessing accuracy lift


q: Are spectral-channel-count redundancy and continuous launch year collinear within common support (report VIF or partial-R-squared)? Show what NTRS lineage / reprocessing-version history would have to demonstrate to separate over-specification redundancy from obsolescence; if it cannot, concede non-identification.

query_terms: VIF partial R-squared channel count launch year collinearity common support

query_terms: over-specification redundancy versus obsolescence non-identification concede

query_terms: NTRS lineage reprocessing version history separate era channel


q: Channel-count is simultaneously the cost driver g(cost) proxies, a linear control in X, and the do(channel-count) target of the stopping rule; on the DAG it is a parent of cost on cost<-channels->accuracy, so entering channels in X conditions on a mediator. Draw the DAG, decide whether the target is do(cost) or do(channel-count), pick the matching adjustment set, and show the marginal-channel-contribution function is empirically invariant to which collinear decision is conditioned vs treated as the variable of interest.

raised_by: pearl

query_terms: channel count mediator over-control conditioning d-separation DAG

query_terms: marginal channel contribution partition invariance adjustment set

query_terms: mediation formula total versus partial effect collinear design decision


q: Conditioning on 'has a validation record' is collider stratification on a common effect of cost and accuracy (build-quality and mission-stakes raise both cost and the probability of a published validation record), which can manufacture spurious concavity among survivors. State the DAG's testable conditional-independence implications that distinguish a genuine concave frontier from collider-induced bias, test them in the survivor sample, and recover flown-but-unvalidated radiometers (cost records, no published L2/L3 validation) to show curvature is stable when they are reweighted back in (IPSW or Heckman-type correction).

query_terms: collider stratification survivorship validation record spurious concavity

query_terms: endogenous selection bias conditioning common effect reweight recover

query_terms: inverse probability of selection Heckman flown-but-unvalidated radiometer


q: The payoff is interventional (do(channel-count=k), do(reallocate dollars)) yet the estimand is the rung-1 conditional expectation E[accuracy|cost,X] with no do-operator and an admitted reduced-form cost effect; X contains calibration approach and realized cost, both descendants of the channel-count decision. State precisely which do-query the stopping rule asserts, write the adjustment set the DAG requires, and show whether the actual control set equals it or conditions on post-channel-decision mediators (in which case the rule has no interventional license regardless of how reliably negative g''). Options: reduce X to a valid back-door set, invoke front-door through cost, or restate as non-actionable association.

query_terms: do-operator back-door front-door adjustment set interventional license

query_terms: over-control realized cost calibration descendant channel decision mediator

query_terms: seeing versus doing reduced-form non-actionable stopping rule


q: Section 4.4 names two unobserved confounders with opposite bias directions yet 5.2 still emits a binary H1/H0 verdict from a point estimate. When you cannot identify, bound: run a Rosenbaum/E-value sensitivity analysis on the assembled table and report the smallest confounder-to-cost and confounder-to-accuracy association strength that flips the sign of g'' over common support. If a confounder comparable to the retrieval-difficulty control suffices, the headline is not identified and must be a bound, not a verdict.

query_terms: E-value Rosenbaum sensitivity break-even confounder flip g'' sign

query_terms: partial identification bound not verdict opposite bias confounders

query_terms: smallest association strength cost accuracy overturn concavity


q: Requirement and reference-precision are descendants of the same selection that sets cost, so requirement-normalization plus reference-ceiling flattening can be collider/mediator conditioning that manufactures concavity. From the assembled DAACs/cal-val records build the raw-error (un-normalized, native-unit, within-family) outcome and show the g'' sign survives, and partition rows by whether the validation reference sits at its documented precision limit to show high-cost flattening is not the reference ceiling masquerading as a frontier.

query_terms: raw native-unit error within-family outcome g'' sign survives normalization

query_terms: validation reference precision limit ceiling partition high-cost flattening

query_terms: requirement-normalization descendant selection collider mediator manufactured concavity


q: Produce the explicit DAG over the named variables (cost, channel count, difficulty, epoch, calibration, mass, power, accuracy), derive its d-separation-implied conditional independencies (e.g. accuracy independent of mass given cost and difficulty if mass acts only through cost), and run those tests on the assembled table; if the data reject an implied independence the back-door adjustment set in 4.2 is wrong and the concavity estimate inherits the misspecification. The words mediator and collider appear zero times in the current text.

query_terms: explicit DAG d-separation implied conditional independence test adjustment set

query_terms: back-door set asserted not derived falsifiable before estimation

query_terms: credible directed acyclic graph causal inference adjustment-set selection


q: Show the assembled table has a non-trivial mass of rows with requirement-normalized accuracy strictly interior to the compliance cap (exceeding requirement by a cost-varying margin), so g'' is identified off interior variation rather than off ceiling-pinned products, and report what fraction of high-cost rows sit at the compliance boundary versus below it, with per-family validation-reference precision limits overlaid to separate a real frontier from mechanical ceiling saturation of a bounded metric.

query_terms: requirement-normalized accuracy interior mass compliance cap histogram

query_terms: g'' identified off interior versus ceiling-pinned saturation bounded metric

query_terms: high-cost rows compliance boundary versus interior reference precision overlay


q: Name the aspiration level (the mission Level-1 accuracy requirement at formulation) each design organization satisficed against, recover it from the NTRS/requirements record, and test whether the located over-specification edge coincides with that aspiration threshold rather than with generic cost curvature, since only the former is the Simon satisficing mechanism. The candidate locates the edge in spectral-channel count, not at a recovered per-instrument aspiration threshold.

query_terms: aspiration level Level-1 requirement formulation recover NTRS requirements record

query_terms: satisficing stopping rule recoverable threshold versus diminishing returns

query_terms: edge-versus-aspiration coincidence test spectral channel count


q: Build from NTRS channel center-wavelengths and bandpasses a direct spectral-redundancy measure (information content / inter-channel correlation per retrieval) and show that the channel count where the regression's marginal channel contribution goes to zero coincides with the count where measured redundancy saturates, with calibration drift and geolocation entered as separately measured controls, so the flattening is demonstrably channel redundancy and not an omitted cost-correlated driver the reduced form cannot separate.

query_terms: direct spectral redundancy measure inter-channel correlation information content per retrieval

query_terms: marginal channel zero coincides measured redundancy saturation count

query_terms: calibration drift geolocation separate control omitted cost-correlated driver


q: Estimate the density of requirement-normalized accuracy around each product family's requirement and report whether the bunching mass just at-or-above 1.0 is non-zero (the satisficing signature), since without that test the curve's shape is attributed to satisficing while measuring nothing satisficing predicts. Concavity is otherwise equally consistent with a physical information-saturation ceiling.

query_terms: bunching estimator density requirement-normalized accuracy threshold 1.0 satisficing signature

query_terms: satisficing behavioral signature versus physical information saturation ceiling

query_terms: density per product family requirement attainment thinning above


q: Construct from NICM/NTRS a direct cross-subsystem coupling / integration-burden proxy (share of cost or schedule attributable to integration-and-test vs component build, or count of calibration-subsystem interfaces) and show whether the over-specification edge coincides with rising coupling burden rather than merely high channel count. If the flat region is channel-count redundancy with no rise in coupling burden, the specific near-decomposability mechanism is falsified even if concavity holds.

query_terms: integration and test cost share component build coupling burden proxy NICM

query_terms: near-decomposability cross-subsystem coupling versus within-subsystem channel count

query_terms: calibration subsystem interface count over-specification edge coincide


q: Re-specify the over-specification test to interact the marginal channel-count contribution with each product's distance from its own stated requirement and report whether the marginal contribution goes to zero once the requirement is met (satisficing, curvature keyed to distance-to-requirement) rather than uniformly at high cost (generic concave technology). Without showing the edge tracks requirement-attainment across families with different requirements, the region is a property of the cost technology, not bounded-rational design behavior.

query_terms: marginal channel contribution interact distance to requirement attainment collapse

query_terms: satisficing curvature keyed requirement met versus uniform high cost

query_terms: requirement-keyed collapse across families different requirements generic concave


q: MODERATOR MISSING ANGLE: every panelist attacked the identification, measurement, mechanism, and rival facets, but no seat interrogated the ECONOMICS / WELFARE facet directly: whether the dollars 'saved' by capping at the over-specification edge are actually reallocable within the real budget and appropriation structure, what the elasticity of accuracy with respect to reallocated dollars is, and whether the welfare claim survives the foregone-discovery cost (Hayek) plus the program-of-record rigidities (North) jointly. Phase 1 must source the cost-reallocation and opportunity-cost economics that converts a fitted frontier into a defensible budget-stakes claim.

facet: economics

raised_by: moderator

query_terms: budget reallocation opportunity cost satellite instrument descope appropriation rigidity

query_terms: elasticity accuracy reallocated dollars distributed mission portfolio welfare

query_terms: value of information Earth observation cost-benefit over-specification welfare


q: PRIORITY/DECISION-RELEVANCE: the contribution's stakes rest on per-instrument capability choices being made now under fixed toplines, but no panelist sourced the decision-cadence evidence that a stopping rule would actually be consulted at formulation (who holds the descope authority, at which milestone, against which cost tool). Phase 1 should ground the decision-process claim so the assurance-case 'material' subclaim is warranted by an institutional decision pathway, not only by the existence of tradespace tools.

facet: priority

query_terms: instrument formulation milestone descope authority decision cadence fixed topline

query_terms: tradespace tool consulted at formulation cost capability decision pathway

query_terms: distributed mission per-instrument capability choice budget decision who decides