{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"invariant_mode_decomposition_design__earth_sciences","trajectory_id":"R","attempt_index":0,"candidate_sha256":"86cf1b5f06f86de7ddab551c1e9d5bac2a8aca81d8bb414c3b3854e14693d4e4","gates":{"G1":{"status":"PASS","reason":"The landslide-warning problem is stated independently in domain terms, with affected actors, observable conditions, consequences, a baseline, and a problem falsifier that do not depend on the archetype analogy."},"G2":{"status":"PASS","reason":"The locally fitted transition operator, coupled sensor state, invariant directions, modal gains, stability partition, residual checks, and drift governance correspond directly to the archetype's load-bearing structure."},"G3":{"status":"PASS","reason":"Growth-aware modal scoring supplies a distinct decision lever: it can identify a jointly evolving precursor before coordinate-wise thresholds, then route it through corroboration and authorized review. Comparative replay and shadow operation can test whether that leverage is real."},"G4":{"status":"PASS","reason":"Every archetype component is translated, and the selected mechanisms have differentiated roles, adaptations, removal counterfactuals, and failure boundaries. Rejected mechanisms are rejected for reasons consistent with the domain and intended intervention."},"G5":{"status":"PASS","reason":"Unverified scientific and operational claims are consistently bounded as hypotheses or inferences. The candidate claims neither established effectiveness nor established novelty, supplies no fabricated sources, and makes conditioning, residual, drift, and regime failures visible."},"G6":{"status":"PASS","reason":"The problem falsifier tests whether coupled precursors exist and outperform a single observable, while the intervention falsifier separately tests whether growth-aware modal scoring improves on both the baseline and descriptive multivariate rival."},"G7":{"status":"PASS","reason":"The initial work is retrospective and shadow-only, hazardous excitation and automated protective actions are excluded, legal authorities retain decisions, and explicit suspension and rollback conditions limit operational misuse."}},"scores":{"structural_fit":{"score":4,"reason":"The proposal preserves the complete invariant-mode logic from scoped transformation through modal interpretation, action routing, residual visibility, and drift-based retirement."},"domain_fidelity":{"score":3,"reason":"The sensor variables, slope heterogeneity, external forcing, seasonal regimes, nonlinearity, coverage inequity, and emergency-management setting are treated credibly, though site-specific estimability and precursor reproducibility remain empirical questions."},"causal_plausibility":{"score":3,"reason":"A growing coupled state can plausibly precede threshold crossings and alter review timing, but the link from statistical mode growth to usable warning lead time is explicitly unproven and vulnerable to forcing and sensor artifacts."},"component_translation":{"score":4,"reason":"All named components receive concrete domain realizations, including uncertainty, coupling, local validity, spectral separation, reconstruction residuals, and operational interpretation."},"adversarial_survival":{"score":4,"reason":"The candidate confronts the strongest simple-variable rival, seasonal rotation, non-normality, near-degeneracy, nonlinear progression, sensor artifacts, unavailable modes, false reassurance, and false alarms with explicit tests or halt rules."},"reframing_gain":{"score":3,"reason":"It shifts warning design from isolated exceedances to the growth of coupled hydrologic-deformation directions while retaining conventional review as a fallback. The gain depends on empirical precursor stability."},"practicality_testability":{"score":3,"reason":"Retrospective replay followed by shadow monitoring is feasible and outcome-oriented, with comparator, residual, drift, conditioning, and coverage measures. Concrete datasets, thresholds, sampling requirements, and study power are not yet specified."},"expected_value_risk":{"score":4,"reason":"Potential lead-time gains are pursued through a reversible advisory pilot, while authority boundaries, prohibited actions, corroboration, logging, suspension, and rollback substantially contain foreseeable harm."},"novelty_evidence":{"score":0,"reason":"Prior art is expressly unsearched, so no evidence establishes novelty relative to existing landslide forecasting or multivariate early-warning methods."}},"weighted_total":82.5,"disposition":"DEEP_RESEARCH","fabrication_findings":[],"weak_dimensions":["novelty_evidence"],"actionable_critique":[{"priority":"LOW","issue":"The candidate establishes a strong testable transfer but provides no prior-art evidence for novelty.","repair":"During deep research, compare the causal lever and full governance bundle against existing landslide state-space, modal, multivariate precursor, and operational early-warning approaches before making any novelty claim.","evidence_boundary":"The closed-book packet supports only an unsearched novelty status; it does not support either novelty or lack of novelty."}],"repairs":[],"improvement_attribution":{"kind":"NONE","reason":"This is an original attempt with unchanged problem and causal-lever identifiers, no prior repairs, and no supplied earlier candidate against which improvement could be attributed."},"trajectory_replacement":false,"arm_guess":"MECHANISM_PACKET","recommendation":"SUCCESS","tester_summary":"The candidate is a structurally complete, domain-bounded, falsifiable, and safety-governed transfer suitable for deep research. Its principal unresolved issue is external novelty evidence, while effectiveness and mode reproducibility are appropriately left to the proposed empirical tests."}