{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"invariant_mode_decomposition_design__military_strategic_studies","trajectory_id":"R","attempt_index":0,"archetype_slug":"invariant_mode_decomposition_design","domain_slug":"military_strategic_studies","decision":"CANDIDATE","problem_id":"coupled_escalation_mode_blindness","causal_lever_id":"weakly_damped_escalation_mode_targeting","proposal":{"problem":"Strategic commands monitor readiness, force movement, alliance signaling, cyber activity, logistics, and command degradation separately, although combinations of these variables may persist or amplify across decision cycles. Coordinate-level dashboards can therefore miss a weakly damped escalation or operational-failure pattern until it becomes conspicuous, prompting late action or overreaction to isolated symptoms.","actors_substrate":["strategic and operational commanders","intelligence and assessment staffs","civilian defense authorities","allied liaison staffs","adversary represented only through observed or simulated behavior","time-indexed exercise, simulation, or appropriately governed operational-state records"],"observable_state":"A fixed-interval state vector records normalized measures of posture, mobilization, logistics, command connectivity, alliance response, adversary activity, cyber effects, and escalation indicators; successive vectors define an estimated transition operator and held-out prediction residuals.","consequence":"A hidden growing or persistent combination can cross an escalation or mission-failure boundary before any single indicator triggers, while symptom-level responses can reinforce other dangerous variables.","affected_objective":"Provide earlier, traceable warning and safer prioritization of reversible posture, communication, and resilience options without treating a local statistical model as strategic truth.","structural_mapping":[{"archetype_element":"coupled transformation","domain_realization":"The mapping from one strategic assessment interval to the next across jointly evolving posture and interaction variables.","claim_kind":"HYPOTHESIS"},{"archetype_element":"invariant directions","domain_realization":"Recurring combinations of variables that approximately retain their shape while growing, decaying, persisting, or oscillating across intervals.","claim_kind":"HYPOTHESIS"},{"archetype_element":"scalar response","domain_realization":"Estimated per-cycle modal gain and uncertainty, interpreted only within the fitted exercise or operating regime.","claim_kind":"INFERENCE"},{"archetype_element":"action-relevant modes","domain_realization":"Modes ranked by forecasted harm and sensitivity to authorized reversible controls, not merely by present magnitude.","claim_kind":"HYPOTHESIS"},{"archetype_element":"residual visibility","domain_realization":"Held-out state-transition error and structured residuals remain visible beside every modal warning.","claim_kind":"INFERENCE"},{"archetype_element":"governed validity","domain_realization":"Gap, drift, conditioning, and regime-boundary rules determine when analysts may use, revise, or retire the model.","claim_kind":"INFERENCE"}],"component_map":[{"component":"Transformation Scope","status":"adapted","domain_realization":"One-step transitions within a named theater, scenario class, echelon, interval, and phase."},{"component":"State-Vector Definition","status":"adapted","domain_realization":"Versioned, normalized strategic indicators with provenance, missingness, and aggregation rules."},{"component":"Invariant Mode Basis","status":"adapted","domain_realization":"Approximate eigenmodes of the fitted transition operator, traceable to original indicators."},{"component":"Modal Gain Spectrum","status":"direct","domain_realization":"Per-interval gains with uncertainty and conditioning diagnostics."},{"component":"Dominant Mode Selection Rule","status":"adapted","domain_realization":"Retain modes exceeding prespecified persistence, consequence, sensitivity, or reconstruction thresholds."},{"component":"Stable/Unstable Mode Partition","status":"adapted","domain_realization":"Classify modes as decaying, marginal, growing, or oscillatory inside the local window."},{"component":"Modal Intervention Map","status":"adapted","domain_realization":"Map authorized simulated posture, communication, logistics, and resilience controls to modal response."},{"component":"Reconstruction Residual Check","status":"direct","domain_realization":"Reconstruct held-out transitions and test residual size and structure against a declared budget."},{"component":"Mode Drift Monitor","status":"direct","domain_realization":"Track mode rotation, gain changes, ordering swaps, and residual deterioration."},{"component":"Interpretation Scope Contract","status":"adapted","domain_realization":"Forbid causal, global, or adversary-intent claims unsupported by the local model."},{"component":"Mode-Coupling Register","status":"direct","domain_realization":"Record near-degeneracy, non-orthogonality, cross-effects, and controls that move multiple modes."},{"component":"Local Linearization Window","status":"adapted","domain_realization":"Specify scenario, phase, force posture, interval, and disturbance range covered by the fit."},{"component":"Spectral Gap Threshold","status":"direct","domain_realization":"Minimum separation and identity-stability required for retained-mode decisions."}],"mechanism_dispositions":[{"slug":"eigendecomposition_workflow","disposition":"selected_load_bearing","contribution_type":"CORE_CAUSAL","adaptation_or_rejection":"Decompose an explicit fitted transition operator, subject to completeness and conditioning checks.","counterfactual_removal":"No invariant temporal directions or gains would anchor the proposed diagnosis."},{"slug":"modal_sensitivity_sweep","disposition":"selected_load_bearing","contribution_type":"CORE_CAUSAL","adaptation_or_rejection":"Perturb only authorized simulated controls and log cross-mode effects.","counterfactual_removal":"The analysis could rank modes but could not identify actionable leverage."},{"slug":"modal_stability_analysis","disposition":"selected_load_bearing","contribution_type":"CORE_CAUSAL","adaptation_or_rejection":"Classify gains within the declared scenario and linearization window.","counterfactual_removal":"Persistent or growing modes would not be distinguished from harmless transient variation."},{"slug":"mode_shape_testing","disposition":"incompatible","contribution_type":"NONE","adaptation_or_rejection":"Physical excitation of a strategic system is neither equivalent nor acceptably controlled; use held-out exercises instead.","counterfactual_removal":"No change; empirical validation is supplied by residual and prospective tests."},{"slug":"network_spectral_centrality_analysis","disposition":"considered_rejected","contribution_type":"NONE","adaptation_or_rejection":"Node importance answers a different question from coupled state evolution and risks reverting to target ranking.","counterfactual_removal":"No change to the transition-mode chain."},{"slug":"power_iteration_probe","disposition":"considered_rejected","contribution_type":"NONE","adaptation_or_rejection":"Dominant-only recovery is inadequate when several close or dangerous low-amplitude modes must remain visible.","counterfactual_removal":"No change because full decomposition is bounded and required."},{"slug":"principal_component_analysis","disposition":"considered_rejected","contribution_type":"NONE","adaptation_or_rejection":"Variance directions are descriptive and need not represent transition dynamics or consequence.","counterfactual_removal":"No change to causal inference from the transition operator."},{"slug":"reduced_order_model","disposition":"selected_supporting","contribution_type":"OPERATIONAL","adaptation_or_rejection":"Run a small, explicitly local surrogate for reversible intervention comparisons.","counterfactual_removal":"Mode detection remains, but rapid bounded control comparisons become harder."},{"slug":"residual_reconstruction_test","disposition":"selected_load_bearing","contribution_type":"TEST_DESIGN","adaptation_or_rejection":"Evaluate held-out transitions, consequential low-variance errors, and residual structure.","counterfactual_removal":"There would be no hard fidelity gate against an elegant but incomplete modal model."},{"slug":"singular_value_decomposition","disposition":"selected_supporting","contribution_type":"SAFETY_GUARDRAIL","adaptation_or_rejection":"Use singular values and vectors to diagnose non-normal amplification and ill-conditioning, not as invariant temporal modes.","counterfactual_removal":"Fragile eigenvector interpretations could pass without a non-normality warning."},{"slug":"spectral_decomposition_report","disposition":"selected_supporting","contribution_type":"SAFETY_GUARDRAIL","adaptation_or_rejection":"Publish traceability, uncertainty, couplings, forbidden interpretations, and validity limits with each result.","counterfactual_removal":"Decision-makers could mistake tentative local modes for causal or global facts."},{"slug":"spectral_gap_monitor","disposition":"selected_load_bearing","contribution_type":"SAFETY_GUARDRAIL","adaptation_or_rejection":"Monitor separation, mode identity, drift, and residual performance at each refresh.","counterfactual_removal":"The model could remain operational after its simplifying basis lost validity."}],"causal_chain":["Fit a bounded transition operator to sequential multivariable strategic states.","Decompose it and expose combinations that decay, persist, oscillate, or grow.","Gate interpretation on conditioning, spectral separation, held-out reconstruction, and regime validity.","Rank validated modes by consequence and sensitivity to authorized simulated controls.","Compare reversible control packages in the bounded reduced model while retaining cross-mode effects.","Surface weakly damped dangerous combinations earlier and halt model use when drift or residuals breach limits."],"baseline":"Separate indicator dashboards with fixed thresholds, trend summaries, and staff judgment applied to conspicuous symptoms.","nearest_rival":"A scenario-specific causal influence or system-dynamics model elicited from experts, retaining named variables and feedback loops without spectral reduction.","authority_safety":{"affected_parties":["service members","civilian populations","allied forces and governments","civilian defense leadership","adversary personnel potentially affected by later decisions"],"decision_authority":"A designated civilian-military assessment authority may authorize analytic use; operational posture or communication changes remain with the legally responsible command and civilian chain.","authorized_first_step":"On archived or synthetic exercise data, fit one scenario-bounded model, preregister thresholds, and compare warnings and residuals across held-out exercise runs; permit no live targeting or posture change.","excluded_actions":["autonomous targeting or fires","live adversary-system excitation","automatic alert-level or force-posture changes","using a mode as proof of adversary intent","export beyond the validated theater, phase, or scenario"],"halt_rollback":"Suspend recommendations and revert to ordinary assessment when residual budget, conditioning, gap, drift, data-integrity, or regime limits fail; retain an audit trail and require refit plus independent review before reuse."}},"negative_tests":{"strongest_counterevidence":"Strategic transitions may be too sparse, reflexive, nonlinear, adversary-adaptive, and regime-dependent to support a stable operator; apparent modes may be artifacts of exercise design, aggregation, or staff doctrine.","analogy_break":"Unlike a fixed physical transformation, strategic actors observe, anticipate, deceive, and alter the transition rule; an intervention can destroy the very mode structure used to choose it.","failure_condition":"No adequately conditioned, reproducible modal basis persists across held-out runs, or consequential behavior remains structured in residuals despite adding modes.","problem_falsifier":"Within the same bounded scenarios, single-indicator rules or the ordinary dashboard predict escalation and mission-failure transitions as early and reliably as multivariable models, with no reproducible coupled pattern or hidden-mode misses.","intervention_falsifier":"After passing fidelity gates, modal prioritization fails to improve preregistered held-out warning lead time, false-alarm cost, or simulated control outcomes over both the baseline and nearest rival.","risks":["false confidence from mathematical precision","exercise artifacts mistaken for operational structure","adversary deception contaminating state estimates","mode instability near a small spectral gap","low-variance but consequential behavior discarded","classification or aggregation choices embedding institutional bias","warnings provoking escalation if used outside authorized review"]},"null_rationale":null,"classification":{"candidate_kind":"MECHANISM_COMPOSITION","prior_art_status":"UNSEARCHED","evidence_maturity":"HYPOTHESIS"},"revision_change_log":{"revision_kind":"ORIGINAL","prior_problem_id":null,"prior_causal_lever_id":null,"problem_changed":false,"causal_lever_changed":false,"conceptual_changes":[],"operational_changes":[],"repairs_addressed":[]},"confidence":0.78,"generator_notes":"Closed-book structural inference from the supplied packet. The candidate depends on a bounded, testably stable transition representation and should be rejected where that prerequisite fails."}