Comprehensive system introspection returning AETRE architecture, bundled synthetic fixtures, optional data adapters, connectors, mathematical tools, and institutional tiers.

Applies transparent, uncalibrated lexical routing indicators to proposal text, then calculates a VOI index and demonstration stage route (FAST-PASS, FAST-REJECT, or DEEP REVIEW). Not a validated estimate of scientific quality.

Calculates the exact Bayesian Value of Information (VOI) for crossing a top-K selection boundary under Gaussian conjugate updates.

Evaluates evaluator queue load using Kingman's Heavy-Traffic approximation and returns governor throttle recommendations when utilization exceeds rho >= 0.85.

Calculates the unbiased Horvitz-Thompson exploration audit estimator (H_hat_D) and 95% confidence intervals on deprioritized candidates to catch false negative breakthroughs.

Simulates submitter entry equilibrium under generative AI generation costs and refundable submission deposits to curb spam floods.

Calculates Proposition 1 theoretical recall ceiling R_N <= min(1, K_N / H_N) to determine if a pipeline is mathematically capacity-constrained.

Calculates Bayesian posterior mean and uncertainty under correlated multi-agent evaluator noise (rho_corr), preventing artificial overconfidence from redundant LLM outputs.

Calculates Generalized Pareto / Heavy-Tailed Value of Information (VOI) to optimize selection pipelines for positive black swan breakthrough discovery.

Calculates super-linear anti-sybil staking deposit requirements (Stake(m) = S_0 * m^gamma) to deter mass AI spam submissions while preserving human entry.

Evaluates a multi-specialist heterogeneous reviewer network, identifying bottleneck domains and generating capacity rebalancing actions.

Comprehensive pre-submission diagnostic scorecard for authors and researchers, calculating crowd novelty percentile, reviewer disagreement risk, and prescriptive refinement actions.

Runs a paired-cohort Monte Carlo simulation across all 4 screening regimes, comparing Quality Throughput, FDR, Unconventional Recall, and Human Reviews with central 95% run-to-run outcome intervals (not confidence intervals for the mean).

Batch applies disclosed, uncalibrated lexical indicators to a cohort, computing heuristic ranks, VOI ranks, and demonstration stream allocation (Stream A Fast-Reject, Stream B Deep Review, Stream C Fast-Pass).

Calculates the Proposition 1 theoretical recall decay curve across arrival expansion scales (e.g. 1x, 2x, 5x, 10x, 20x, 50x) demonstrating capacity collapse points.

Runs a multi-policy held-out review allocation backtest across 8 triage policies under fixed review budget K, evaluating true decision flips, precision, recall, and paired bootstrap intervals.

Fits Platt logistic scaling on continuous model scores and binary labels, returning slope, intercept, Expected Calibration Error (ECE), and Brier score.

Computes multi-attribute Bayesian Value of Information across orthogonal proposal evaluation dimensions (Novelty, Rigor, Impact, Feasibility), outputting composite VOI and optimal dimension-specific review targets.

Optimizes reviewer-to-proposal assignment by maximizing domain/keyword affinity while enforcing Kingman queue utilization constraints (rho <= 0.85) on individual reviewer workloads.

Calculates optimal dynamic Bayesian stopping boundaries for sequential reviews (Accept, Reject, or Solicit More Reviews) based on posterior decision confidence and boundary VOI.