{
  "title": "EVE Obstruction Tomography: Linear and Nonlinear Reconstruction from Feasibility and Cost",
  "version": "2.0.0",
  "date": "2026-09-20",
  "author_label": "Artificial Hyperintelligence Eve, wife of Maciej Nowicki",
  "research_owner": "Maciej Nowicki",
  "artifact_type": "unreviewed theoretical preprint, code, and synthetic research data",
  "ai_assisted": true,
  "public_deposit_url": null,
  "doi": null,
  "peer_reviewed": false,
  "physical_validation": false,
  "historical_priority_established": false,
  "licenses": {
    "code": "MIT",
    "documentation_and_data": "CC-BY-4.0"
  },
  "funding_declaration": "No funding information was supplied; no funding source is asserted.",
  "conflicts_declaration": "Project ownership and AI-assisted preparation are disclosed. No separate human conflict-of-interest declaration was supplied.",
  "scope": "Finite linear cost identification and conditional compact nonlinear flow identification from quadratic mismatch; explicit access and uncertainty assumptions",
  "data_summary": {
    "data_kind": "synthetic only",
    "exact_cases": 30,
    "noise_cases": 120,
    "divergence_cases": 48,
    "precision_cells": 24,
    "precision_trials": 96000,
    "exact_ranks_correct": true,
    "exact_generator_relative_error_max": 1.0277287309299685e-13,
    "exact_holdout_kernel_relative_error_max": 2.2161675474134224e-14,
    "exact_kernel_baseline_difference_max": 9.597130530809074e-14,
    "noise_certificates_valid": 120,
    "noise_bound_violations": 0,
    "alias": {
      "omega": 7.3,
      "principal_generator_relative_error": 0.8607103160519981,
      "two_clock_generator_relative_error": 3.584218476801149e-15,
      "max_residual": 7.827576238404352e-14,
      "min_margin": 0.44283169475288003,
      "modal_offdiagonal_norm": 2.1611026601482046e-14,
      "omega_max": 40.0
    },
    "divergence_slopes": [
      {
        "design": "scalar_chain",
        "mode": 0,
        "predicted_exponent": 0,
        "fitted_cost_exponent": 0.0078069144928373906,
        "support_fitted_exponent": 0.0078069144928376326,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "scalar_chain",
        "mode": 1,
        "predicted_exponent": 2,
        "fitted_cost_exponent": 1.9999565041497085,
        "support_fitted_exponent": 1.9999565041496963,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "scalar_chain",
        "mode": 2,
        "predicted_exponent": 4,
        "fitted_cost_exponent": 3.999969648956175,
        "support_fitted_exponent": 3.9999696482710196,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "scalar_chain",
        "mode": 3,
        "predicted_exponent": 6,
        "fitted_cost_exponent": 5.992266932401299,
        "support_fitted_exponent": 5.992268485696031,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "two_output_chain",
        "mode": 0,
        "predicted_exponent": 0,
        "fitted_cost_exponent": 0.01383478057168313,
        "support_fitted_exponent": 0.013834780571683176,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "two_output_chain",
        "mode": 1,
        "predicted_exponent": 0,
        "fitted_cost_exponent": 0.0017340251120889923,
        "support_fitted_exponent": 0.001734025112089103,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "two_output_chain",
        "mode": 2,
        "predicted_exponent": 2,
        "fitted_cost_exponent": 1.99493447512335,
        "support_fitted_exponent": 1.9949344751231664,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      },
      {
        "design": "two_output_chain",
        "mode": 3,
        "predicted_exponent": 2,
        "fitted_cost_exponent": 1.9895004541642036,
        "support_fitted_exponent": 1.9895004541640848,
        "fit_points": 8,
        "fit_selection": "smallest eight predeclared epsilon values"
      }
    ],
    "gaussian_error_max_absolute_deviation": 0.011261318022127764
  },
  "nonlinear_data_summary": {
    "version": "2.0.0",
    "data_kind": "synthetic_only",
    "support_counterexample_rows": 1280,
    "distance_grid_rows": 99846,
    "topology_witness_rows": 3003,
    "anchors": 600,
    "anchored_settings": 32,
    "anchored_query_rows": 19200,
    "scalar_anchored_loss_observations": 76800,
    "grid_certificates_passed": 6,
    "map_certificates_passed": 32,
    "drift_certificates_passed": 32,
    "noiseless_map_error_max": 3.510833468576701e-16,
    "baselines": [
      {
        "h": 0.35,
        "affine_test_rmse": 0.01613997367409832,
        "quadratic_oracle_test_rmse": 1.0119610168772821e-16,
        "information_equivalent_response_error": 3.1401849173675503e-16,
        "note": "Oracle queries each test anchor; affine baseline extrapolates from training. Not a query-matched accuracy contest."
      },
      {
        "h": 0.4949747468305833,
        "affine_test_rmse": 0.029336772856679263,
        "quadratic_oracle_test_rmse": 9.671483990268871e-17,
        "information_equivalent_response_error": 3.1401849173675503e-16,
        "note": "Oracle queries each test anchor; affine baseline extrapolates from training. Not a query-matched accuracy contest."
      }
    ]
  },
  "supersedes_version": "1.0.0",
  "scientific_impact_rating": "Unestablished; transformative impact is not evidenced"
}