docs(gap): refresh operator-gap register against post-#239 protected main

CHANGELOG.md

@@ -36,6 +36,7 @@ All notable changes to TEPP are documented here. The format follows Keep a Chang
 
 ## [Unreleased]
 
+- Operator-gap register refreshed against protected main `c482ccea` (#239): workspace version 0.2.0, 57 crates, queue at seven open PRs with exact-head SHAs, issues #156/#168/#175 closed, GAP-009 advanced to estimator-core-plus-repairs with Leiden consensus remaining, GAP-001/GAP-012/GAP-017 closed on protected main, and a new Post-#239 state note recording both the estimator repairs and the non-release status of the version bump. Supersedes #236 whose base predated #239.
 - Restored protected-main gate integrity after the consolidation merges: hourly-scheduler prompt-contract tests now assert the gap-baseline-derived task contract (Gap ID naming, no invented weights) instead of stale increment-specific tokens, the operator-gap register inventory matches the live 33-PR queue, `evidence_core::image_unit` non-image/empty-subtype refusals and `load_union_branch_totals` valid-record accumulation have exact coverage, and the README crate fence plus duplicate registry entries stay deduped.
 - Branch-coverage diagnostics on the post-consolidation head exposed two uncovered outcomes in `evidence_core::image_unit` (`is_image_media_type_token` non-image prefix and empty-subtype refusals), one uncovered authored line (the strip-prefix refusal), and lost valid-record coverage for `load_union_branch_totals`; exact red-to-green cases now cover the non-image/empty-subtype data URIs and per-coordinate True/False accumulation.
 - Repaired post-consolidation merge fallout that left protected `main` red: restored the lost `return True` in the `check_coverage.py` match-guard branch, removed the shadowed duplicate `load_union_branch_totals` and `_is_multiline_match_guard` definitions plus duplicate workspace-crate entries (`episode_membership`, `analysis_engine`) from the contract tuple and Cargo member arrays, split two union-fused four-tuples back into `(variant, message)` pairs in the `event_core` error table, repaired the fused `identity_recovery_rate` body in `episode_membership::window`, deduplicated the checked-arithmetic eligible-count block in `analysis_engine`, fixed four-argument `unit()` test call sites, rebalanced the README crate-list fence around all 54 unique crates, and deduplicated the `location_membership`/`validation_core`/`tepp_api` architecture-table rows. Also documents private `PLAUSIBLE_IMAGE_MEDIA_TYPES` so `cargo doc -D warnings` passes.
@@ -46,10 +47,6 @@ All notable changes to TEPP are documented here. The format follows Keep a Chang
 - `psychometric_core` executes the later `|| !log_rate.is_finite()` operand on `recover_discrete_time_independent_predictor_effect` from both the lib tests and the multilevel integration crate. Nightly branch coverage on #49 head `90b08bbe82cbe7776365a6c04df38857dfe5e53c` was 1714/1716: both True arms at `event_time.rs` L2480 were unhit because fail-closed tests supplied a non-finite `TIPREDEFFECT` or predictor before `a`. Direct `a = NaN` now takes those arms. `LagClock::as_str` is called through `black_box` so the outlined instantiation is not const-folded away. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, and not ctsem estimation.
 - `psychometric_core` evaluates the Driver, Oud, and Voelkle (2017, §7.2) extra-process lag as `e^{ε Δt}` even when `ε Δt` underflows to `0` (`exp(0) = 1`). Nightly branch coverage on #49 head `22b8e68813ad59a9a91689bacfa4cf033dfad158` was 1718/1720: LLVM deleted `if extra_argument == 0.0` / `original_argument == 0.0` True after proving `ε < 0` and `Δt > 0` imply a nonzero product, which binary64 underflow falsifies. The public map now uses `exp` directly; `original_log_rate == 0` remains the Brownian `e^{0} = 1` path. Recovery tests assert the §7.2 identity `a_{ηξ} x e^{a Δt}(e^{(ε−a)Δt} − 1)/(ε − a)` on `(-min_subnormal) * 1e-320`. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, and not ctsem estimation.
 - `psychometric_core` recovers the Driver, Oud, and Voelkle (2017, p. 16 `MANIFESTMEANSstd`; Table 2, p. 12; footnote 4; Eq. 5, p. 5; 2017-era ctsem `summary.ctsemFit.R`; JSS PDF re-opened 2026-08-25T05:04Z from https://www.jstatsoft.org/index.php/jss/article/download/v077i05/1104) scalar standardised manifest mean. Page 16 prints standardised matrices with the suffix `std` when appropriate. Footnote 4 standardises using only the relevant variance, not the total. Table 2 names `MANIFESTMEANS` `τ` the `n.manifest × 1` matrix of manifest means. Table 2 names `MANIFESTVAR` `Θ` the residual covariance of the indicators. The relevant variance for that named measurement intercept is residual `MANIFESTVAR` `θ`, not total observed `Var(y) = λ² Var(η) + θ`, matching `MANIFESTVARstd`. The 2017-era `summary.ctsemFit.R` forms unstandardised `MANIFESTMEANS` as `mxEval(MANIFESTMEANS, mxobj, compute=TRUE)`. That source does not form a `MANIFESTMEANSstd` matrix; the scalar map here is the footnote 4 standardisation of that named intercept: `τ / √θ`. Form strictly positive `θ` first, then divide `τ` by `√θ`. A zero mean is exactly zero. Unstandardised `MANIFESTMEANS` is defined for a zero residual; standardised `MANIFESTMEANS` is not. Zero `θ` has no positive SD and fails closed. Manifest means are an event-time measurement quantity, so a non-event clock fails closed. `MANIFESTMEANS` does not require stable `a < 0`. `MANIFESTVARstd` `θ / θ = 1` recovers the same number when `τ = √θ` and remains a distinct named quantity. `τ / √(λ² Var(η) + θ)` uses total observed variance and is not this residual map. The 2017-era source assigns `dimnames(MANIFESTMEANS)` to `list(manifestNames, manifestNames)` on an `n.manifest × 1` matrix; that assignment is a source bug and is not this map. `T0MEANSstd` `μ_0 / √p_0` recovers the same number when `τ = μ_0` and `θ = p_0` and remains a distinct named quantity. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, and not ctsem estimation. Meredith (1993) remains unread (Unpaywall 2026-08-25T05:04Z: `is_oa: false`, 0 locations; title *Measurement Invariance, Factor Analysis and Factorial Invariance*). Mislevy (1991, *Psychometrika, 56*, 177–196) remains unread (Unpaywall 2026-08-25T05:04Z: `is_oa: false`, 0 locations; title *Randomization-Based Inference about Latent Variables from Complex Samples*).
-- `network_analysis` posterior edge estimation now carries exact two-sided Fisher z-transform p-values against `rho = 0` (erfc evaluated by an all-positive confluent series plus the Laplace continued fraction, locked to libm reference values at 1e-13 relative tolerance), percentile-bootstrap credible intervals and selection fractions over posterior draws, Benjamini–Hochberg step-up admission on those exact p-values instead of the complement of a thresholded fraction, an explicit fail-closed `edge_drop_probability` parameter for consensus co-assignment resampling (replacing a hardcoded 0.1), and honest per-replicate stability admission; the greedy partition helper is renamed to state that it makes no modularity-optimization claim. APA 7 entries added: Benjamini & Hochberg (1995), Efron (1979), Fisher (1921), Hennig (2007), Monti (2003).
-- Restored protected-main gate integrity after the consolidation merges: hourly-scheduler prompt-contract tests now assert the gap-baseline-derived task contract (Gap ID naming, no invented weights) instead of stale increment-specific tokens, the operator-gap register inventory matches the live 33-PR queue, `evidence_core::image_unit` non-image/empty-subtype refusals and `load_union_branch_totals` valid-record accumulation have exact coverage, and the README crate fence plus duplicate registry entries stay deduped.
-- Branch-coverage diagnostics on the post-consolidation head exposed two uncovered outcomes in `evidence_core::image_unit` (`is_image_media_type_token` non-image prefix and empty-subtype refusals), one uncovered authored line (the strip-prefix refusal), and lost valid-record coverage for `load_union_branch_totals`; exact red-to-green cases now cover the non-image/empty-subtype data URIs and per-coordinate True/False accumulation.
-- Repaired post-consolidation merge fallout that left protected `main` red: restored the lost `return True` in the `check_coverage.py` match-guard branch, removed the shadowed duplicate `load_union_branch_totals` and `_is_multiline_match_guard` definitions plus duplicate workspace-crate entries (`episode_membership`, `analysis_engine`) from the contract tuple and Cargo member arrays, split two union-fused four-tuples back into `(variant, message)` pairs in the `event_core` error table, repaired the fused `identity_recovery_rate` body in `episode_membership::window`, deduplicated the checked-arithmetic eligible-count block in `analysis_engine`, fixed four-argument `unit()` test call sites, rebalanced the README crate-list fence around all 54 unique crates, and deduplicated the `location_membership`/`validation_core`/`tepp_api` architecture-table rows. Also documents private `PLAUSIBLE_IMAGE_MEDIA_TYPES` so `cargo doc -D warnings` passes.
 - `psychometric_core` recovers the Driver, Oud, and Voelkle (2017, p. 16 `T0MEANSstd`; Table 2, p. 12; footnote 4; 2017-era ctsem `summary.ctsemFit.R`; JSS PDF re-opened 2026-08-24T22:30Z from https://www.jstatsoft.org/index.php/jss/article/download/v077i05/1104) scalar standardised initial latent mean. Page 16 prints standardised matrices with the suffix `std` when appropriate. Footnote 4 standardises using only the relevant variance, not the total. Table 2 names `T0MEANS` the latent process means at the first time point `T0`. The first-occasion relevant variance is free `T0VAR` `p_0`, not process-dynamics `asymDIFFUSION` `-q / (2 a)`, matching Table 3 `T0TIPREDEFFECTstd`. The 2017-era `summary.ctsemFit.R` forms unstandardised `T0MEANS` as `OpenMx::mxEval(T0MEANS, mxobj, compute=TRUE)`. That source does not form a `T0MEANSstd` matrix; the scalar map here is the footnote 4 standardisation of that named first-occasion mean: `μ_0 / √p_0`. Form strictly positive `p_0` first, then divide `μ_0` by `√p_0`. A zero mean is exactly zero. Unstandardised `T0MEANS` is defined for a zero first-occasion variance; standardised `T0MEANS` is not. Zero `p_0` has no positive SD and fails closed. `T0` is an event-time occasion, so a non-event clock fails closed. Free `T0MEANS` does not require stable `a < 0`. `T0VARstd` `p_0 / p_0 = 1` recovers the same number when `μ_0 = √p_0` and remains a distinct named quantity. `μ_0 / √asymDIFFUSION` uses process-dynamics variance and is not this first-occasion map. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, and not ctsem estimation. Meredith (1993) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Measurement Invariance, Factor Analysis and Factorial Invariance*). Mislevy (1991, *Psychometrika, 56*, 177–196) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Randomization-Based Inference about Latent Variables from Complex Samples*).
 - `psychometric_core` recovers the Driver, Oud, and Voelkle (2017, p. 16 `asymCINTstd`; Eq. 3, p. 4; footnote 4; Table 2, p. 12; 2017-era ctsem `summary.ctsemFit.R`; JSS PDF re-opened 2026-08-24T09:05Z from https://www.jstatsoft.org/index.php/jss/article/download/v077i05/1104) scalar standardised asymptotic continuous intercept. Page 16 prints standardised matrices with the suffix `std` when appropriate. Footnote 4 standardises using only the relevant variance, not the total. `CINT` is the process intercept of individual, or average individual, dynamics, so that relevant variance is within-subject `asymDIFFUSION` `p = −q / (2 a)`. The 2017-era `summary.ctsemFit.R` forms `asymCINT` whenever `verbose = TRUE`, as `-solve(DRIFT) %*% CINT`. That source does not form an `asymCINTstd` matrix; the scalar map here is the footnote 4 standardisation of that named asymptotic intercept: `(-κ / a) / √p`. Form strictly positive `p` first, then the asymptotic intercept, then divide by `√p`. A zero intercept is exactly zero. Unstandardised `asymCINT` is defined for a zero process; standardised `asymCINT` is not. Zero `q` has no positive process SD and fails closed. Lasting `asymDIFFUSION` requires stable `a < 0`. A non-event clock fails closed. `κ / √p` is the continuous intercept standardisation and is not this total-change map. `A^{-1}[e^{A Δt} − I] κ / √p` depends on the event interval and is not this `Δt → ∞` map. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, not `CINTstd`, not `discreteCINTstd`, and not ctsem estimation. Meredith (1993) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Measurement Invariance, Factor Analysis and Factorial Invariance*). Mislevy (1991, *Psychometrika, 56*, 177–196) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Randomization-Based Inference about Latent Variables from Complex Samples*).
 - `psychometric_core` recovers the Driver, Oud, and Voelkle (2017, p. 16 `discreteCINTstd`; Eq. 3, p. 4; footnote 4; Table 2, p. 12; 2017-era ctsem `summary.ctsemFit.R`; JSS PDF re-opened 2026-08-24T05:20Z from https://www.jstatsoft.org/index.php/jss/article/download/v077i05/1104) scalar standardised discrete continuous intercept. Page 16 prints discrete-time transformations for a chosen event interval and, when appropriate, standardised matrices with the suffix `std`. Footnote 4 standardises using only the relevant variance, not the total. `CINT` is the process intercept of individual, or average individual, dynamics, so that relevant variance is within-subject `asymDIFFUSION` `p = −q / (2 a)`. The 2017-era `summary.ctsemFit.R` forms `discreteCINT` whenever `verbose = TRUE`, as `solve(DRIFT) %*% (discreteDRIFT − I) %*% CINT`. That source does not form a `discreteCINTstd` matrix; the scalar map here is the footnote 4 standardisation of that named discrete intercept: `A^{-1}[e^{A Δt} − I] κ / √p`. Form strictly positive `p` first, then the discrete intercept, then divide by `√p`. A zero intercept is exactly zero. Unstandardised `discreteCINT` is defined for growing `a ≥ 0` and for zero diffusion; standardised `discreteCINT` is not. Zero `q` has no positive process SD and fails closed. Lasting `asymDIFFUSION` requires stable `a < 0`. A non-event clock fails closed. A non-positive event interval fails closed. `κ / √p` does not depend on `Δt` and is not this finite-interval map. `(-κ / a) / √p` is the standardised asymptotic intercept and is not this map. Still not a Kalman filter, not a matrix `expm`, not ESEM estimation, not DSEM, not `CINTstd`, and not ctsem estimation. Meredith (1993) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Measurement Invariance, Factor Analysis and Factorial Invariance*). Mislevy (1991, *Psychometrika, 56*, 177–196) remains unread (Unpaywall 2026-08-24T08:02Z: `is_oa: false`, 0 locations; title *Randomization-Based Inference about Latent Variables from Complex Samples*).