{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp06_four_proposal_generalization60_20260803","cell_id":"predictive_residual_processing__environmental_climate","arm":"COMPLETE_PROPOSAL_PORTFOLIO","candidate_id":"prp-peatland-rewetting-residual-sentinel-001","proposal_index":1,"version":0,"title":"Residual Sentinel for Remote Peatland Rewetting","problem":"A remote peatland-rewetting site measures water-table depth, soil moisture, peat temperature, conductivity, rainfall, and equipment status at short intervals. Most observations may follow predictable weather-driven and diurnal patterns, yet transmitting every complete vector consumes limited station energy and communications capacity. Downsampling or fixed exception rules can then obscure the timing and context of a developing drying regime, blocked water control, sensor displacement, or unusual warming.","actors":["Peatland monitoring lead","Field instrumentation technician","Ecohydrology analyst","Land and fire-safety manager","Independent raw-data reviewer"],"observable_state":"For every observation interval, the station has a timestamped raw sensor vector with quality flags; a versioned model prediction conditioned on recent observations, rainfall, and time; a signed residual for each variable; uncertainty and source-reliability estimates; a channel heartbeat; and a record of whether the interval was suppressed, transmitted as residuals, audited in full, or placed in raw fallback. The receiver can compare its reconstructed vector with independently retained raw observations.","consequence":"When routine variation consumes the constrained link, operators must accept lower temporal resolution, delayed delivery, or greater energy use; consequential departures may consequently reach review without enough temporal context or after the condition has persisted.","affected_objective":"Maintain decision-relevant temporal fidelity for detecting and investigating peatland hydrologic or thermal departures while respecting a declared station energy and communications budget.","intervention":"Run matched, versioned predictors at the field station and receiving server for the next multivariate observation. The station subtracts the prediction from the measured vector, scores each residual using measurement uncertainty, source reliability, consequence class, and transmission cost, and sends selected residuals with timestamps, quality flags, model checksum, and reconstruction metadata. The receiver reconstructs each observation as its matching prediction plus the residual. Heartbeats distinguish an expected interval from missing data. Random and risk-stratified full raw windows, scheduled full-state snapshots, and local raw retention independently test reconstruction. Model staleness, structured residual drift, checksum mismatch, cumulative reconstruction-budget breach, missing heartbeat, sensor fault, or a fire-safety signal suspends residual-only operation for the affected scope and invokes raw transmission and human review. Validated residuals may inform a separately approved model revision, but they do not directly operate pumps, weirs, gates, or emergency systems.","structural_mapping":[{"archetype_element":"Prediction target and boundary","domain_realization":"The next timestamped vector of water-table depth, volumetric soil moisture, peat temperature, conductivity, rainfall, and station-health variables at one instrumented peatland plot; units, sampling interval, sensor-quality rules, and allowable reconstruction error are declared before testing."},{"archetype_element":"Generative model with scope and horizon","domain_realization":"A versioned, site-specific short-horizon predictor conditioned only on declared recent sensor history, rainfall context, and time variables; it is not authorized to infer unmeasured ecosystem condition or conditions at other plots."},{"archetype_element":"Expected and actual behavior","domain_realization":"The model commits its predicted vector before the observation is compared; the station separately records the raw measured vector, timestamp, calibration state, and quality flags."},{"archetype_element":"Prediction comparator and residual","domain_realization":"For continuous variables, the station preserves signed observed-minus-predicted differences; missing, out-of-range, and categorical equipment states remain explicit structured residuals rather than being converted to zero."},{"archetype_element":"Precision and consequence weighting","domain_realization":"Residual priority combines magnitude with current sensor uncertainty, calibration status, variable-specific consequence class, persistence, and channel cost, allowing a reliable small thermal departure to outrank a large but low-quality fluctuation."},{"archetype_element":"Residual propagation and reconstruction","domain_realization":"The constrained link carries admitted residuals plus provenance and heartbeat metadata; the server applies them only to the identified predictor version and reconstructs the full observation vector."},{"archetype_element":"Bounded update rule","domain_realization":"Operational predictions may receive bounded parameter corrections from validated residuals, while structural changes, new covariates, and threshold changes require offline replay, review, versioning, and rollback capability."},{"archetype_element":"Synchronization and validity","domain_realization":"Checksums precede residual interpretation, every residual names its generating model, full-state snapshots re-anchor both sides, and expiration rules prevent stale models or predictions from authorizing suppression."},{"archetype_element":"Independent raw audit","domain_realization":"A random baseline sample plus risk-stratified full windows is retained and reviewed through a path that does not use the production reconstruction as ground truth."},{"archetype_element":"Fallback and protected bypass","domain_realization":"Checksum mismatch, missing heartbeat, drift, reconstruction-budget breach, safety-class signal, or failed station-health check forces full raw handling; designated fire indicators and equipment-fault records are never suppressed."}],"mechanism_mapping":[{"mechanism_slug":"predictive_codec","role":"Provides matched prediction, residual encoding, metadata, and receiver-side reconstruction for the multivariate station stream.","counterfactual_removal":"Without it, the design becomes ordinary anomaly alerting or adaptive sampling rather than a reconstructive residual representation."},{"mechanism_slug":"precision_weighted_error_gate","role":"Allocates limited transmission capacity according to uncertainty, reliability, consequence, and cumulative residual error rather than residual magnitude alone.","counterfactual_removal":"Without it, noisy large deviations can crowd out smaller reliable or safety-relevant departures, and suppression lacks an explicit error budget."},{"mechanism_slug":"event_triggered_residual_reporting","role":"Transmits admitted deviations promptly while using authenticated heartbeats to make quiet intervals distinguishable from channel or station failure.","counterfactual_removal":"Without it, residuals are merely stored or inspected later and do not relieve the constrained live channel or improve exception latency."},{"mechanism_slug":"model_version_checksum_handshake","role":"Prevents a residual generated against one predictor from being reconstructed against another and supplies model provenance for late or replayed messages.","counterfactual_removal":"Without it, apparently valid reconstructions can be silently corrupted by predictor desynchronization."},{"mechanism_slug":"periodic_full_state_resynchronization","role":"Re-anchors the receiver to a complete station state on a cadence and whenever drift evidence warrants an early snapshot.","counterfactual_removal":"Without it, packet loss, quantization, or state divergence can accumulate without a bounded recovery interval."},{"mechanism_slug":"shadow_raw_channel_sampling","role":"Compares randomly and risk-stratified sampled raw windows with reconstructed windows through an independent audit path.","counterfactual_removal":"Without it, the system cannot observe signals that its own model and gate consistently suppress."},{"mechanism_slug":"model_drift_monitoring","role":"Tests residual distributions, calibration, reconstruction disagreement, and model age for evidence that the predictive mode is no longer valid.","counterfactual_removal":"Without it, a sustained environmental regime change may be normalized or treated as isolated noise until cumulative error becomes material."},{"mechanism_slug":"raw_signal_fallback_switch","role":"Restores complete observations for the affected station or variable when compatibility, validity, reconstruction, or safety conditions fail.","counterfactual_removal":"Without it, model failure remains trapped inside the same compressed path and completeness cannot be recovered when most needed."},{"mechanism_slug":"surprise_to_action_bridge","role":"Turns a validated residual into an acknowledged investigation assigned to a named monitoring or safety owner, with full context attached.","counterfactual_removal":"Without it, informative departures can remain dashboard artifacts without a defined review or response path."}],"causal_chain":["Short-horizon environmental regularity permits both endpoints to generate the same expected sensor vector.","The field station compares the committed prediction with the provenance-bearing raw observation.","Precision and consequence weighting separates potentially informative mismatch from expected measurement variation under a declared residual-error budget.","Only admitted residuals and reconstruction metadata consume the routine constrained channel, while heartbeats establish that silence is not missingness.","The receiver combines each residual with the compatible model prediction to recover the observation context used by analysts.","Validated departures reach a named reviewer sooner in the stream and can trigger collection of full context, while routine predicted content does not occupy the same attention path.","Independent raw samples, snapshots, and drift tests expose systematic suppression or desynchronization.","Validity failure switches the affected scope to raw observations; reviewed residuals can later revise the predictor through a versioned, reversible update."],"baseline":"A controlled comparator that sends complete sensor vectors at the existing reporting interval under the same link budget, queues packets when capacity is exhausted, and applies separately configured fixed high/low alarms. It uses no shared predictive reconstruction, residual prioritization, or model-driven fallback.","nearest_rivals":["Adaptive sampling that lowers measurement frequency during stable periods and raises it after a threshold crossing; it changes what is observed and may miss between-sample dynamics, whereas the proposal continues local high-frequency observation and changes what is routinely propagated.","Edge anomaly detection that sends labels or alerts only; it can surface exceptions but does not let the receiver reconstruct the monitored vector from a synchronized model plus signed residuals.","Centralized forecasting applied after full-data upload; it can identify forecast errors but does not address the constrained station channel and supplies no residual codec or sender-receiver synchronization.","Fixed change-from-last-value reporting; it transmits deltas but lacks a context-conditioned generative prediction, uncertainty-aware gating, governed updating, independent raw audit, and drift-triggered decompression."],"remaining_contrastive_claim":"The candidate is specifically a governed, reconstructive sender-receiver loop in which model-relative residuals are both the constrained-channel message and bounded learning input, with independent raw auditing and compulsory decompression when the shared prediction ceases to be trustworthy.","authority_safety":{"decision_authority":"The peatland monitoring lead may authorize a shadow test and, with the instrumentation owner, approve model and threshold versions. Land-control changes remain with the land manager, and emergency decisions remain with the designated fire-safety authority.","authorized_first_step":"Conduct a non-operational shadow replay and one-station parallel trial in which the existing raw-data pipeline remains authoritative and the residual path only records proposed transmissions, reconstructions, gates, and fallback decisions.","excluded_actions":["Automatically operate pumps, weirs, drains, sluices, or other water-control infrastructure","Suppress or delete the authoritative raw record during the trial","Use residual output alone to declare ecological recovery, regulatory compliance, or absence of fire risk","Change safety thresholds to meet a bandwidth or alert-volume target","Automatically dispatch or stand down emergency response","Update the production model or thresholds without versioned review"],"halt_rollback":"Halt the residual trial and revert interpretation to the unchanged raw pipeline upon any checksum acceptance error, missing mandatory bypass, unreconstructable audit window, unexplained missingness, repeated fallback oscillation, or evidence that a consequence-relevant signal was suppressed. Preserve trial logs and restore the last approved model and threshold table before any retest."},"negative_tests":{"strongest_counterevidence":"Under the same sampling and review conditions, the complete-vector baseline remains within the actual energy and communications limits and yields equal or better timely identification of review-worthy hydrologic and thermal departures with lower total model, audit, and operator cost.","problem_falsifier":"Direct measurement shows that communication, energy, storage, and analyst attention are not binding at the proposed temporal resolution, or that the station stream is insufficiently predictable for residual messages plus synchronization and audit overhead to cost less than complete transmission.","intervention_falsifier":"In preregistered walk-forward replay or shadow operation, reconstructed audit windows exceed the declared variable-specific fidelity budget, injected packet-loss or version-mismatch cases fail to invoke raw fallback, any mandatory safety-class record is suppressed, residuals retain systematic temporal or regime structure, or total residual-system cost is not below the complete-vector comparator at required fidelity.","risks":["A slowly drying regime could be absorbed into an adapting baseline and cease to appear surprising.","Incorrect uncertainty or consequence weights could systematically suppress a sensor, season, or low-amplitude precursor.","Shared predictor error could create correlated blind spots at the station and server.","Residuals may expose unusual site events more distinctly than full routine streams, creating data-governance concerns.","Frequent fallback or resynchronization could consume more energy and capacity than complete transmission.","Analysts could act on a context-free residual before reviewing the reconstructed and raw window.","Sensor failure or channel loss could be misread as a perfectly predicted interval if heartbeat handling fails."]},"next_evidence_step":"Using one station and a bounded raw record covering a declared period, preregister a walk-forward replay that compares the residual design with the complete-vector baseline under the same simulated link budget. Freeze one model version and threshold table; retain an untouched evaluation segment; include random raw audit windows and scripted packet-loss, checksum-mismatch, stale-model, missing-heartbeat, and safety-bypass tests. Then run a short parallel shadow trial with no operational actions. Record transmitted bytes, an energy proxy, reconstruction error by variable and condition, structured residual tests, suppressed-error mass, audit disagreements, fallback behavior, and reviewer disposition. This step tests feasibility and failure handling only, not ecological benefit or field safety.","prior_art_status":"UNSEARCHED","diversity_from_prior_proposals":"Not applicable because this is proposal_index 1 and no earlier proposal is present in this sealed output.","revision_record":{"parent_version":null,"progress_targets_addressed":["Initial complete proposal","Concrete environmental monitoring problem","Full causal and mechanism mapping","Authority-bounded first evidence","Explicit counterevidence and falsifiers"],"conceptual_changes":["Initial version; no parent proposal"],"operational_changes":["Initial version; defined shadow-only deployment, reconstruction, synchronization, audit, and fallback procedures"],"evidence_changes":["Initial version; specified a bounded walk-forward replay and parallel shadow trial without external evidence"],"claim_changes":["Claims are conditional and contrastive; no novelty, prevalence, demand, or effect-size claim is made"]}}