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README.md

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----
-license: mit
----
+---
+language:
+  - en
+license: mit
+pretty_name: Aviation Avionics Isolation Reset and Containment Mapping v0.1
+dataset_name: aviation-avionics-isolation-reset-containment-mapping-v0.1
+tags:
+  - clarusc64
+  - aviation
+  - avionics
+  - containment
+  - recovery
+  - redundancy-management
+  - safety
+task_categories:
+  - tabular-classification
+  - tabular-regression
+size_categories:
+  - n<1K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train.csv
+      - split: test
+        path: data/test.csv
+---
+
+# Aviation Avionics Isolation Reset and Containment Mapping
+
+## Purpose
+
+This dataset models how avionics systems should respond after divergence or fault detection.
+
+Detection alone does not prevent failure.  
+The response determines whether the system stabilizes or cascades.
+
+This dataset trains systems to choose the correct containment and recovery strategy.
+
+## Core concept
+
+Once redundant avionics systems diverge, the system must decide:
+
+- which unit to isolate  
+- whether to reset  
+- how to prevent propagation  
+- how to preserve redundancy  
+
+Incorrect containment can:
+- propagate corruption  
+- remove healthy systems  
+- overload pilots  
+- escalate into failure  
+
+The dataset focuses on optimal containment decisions.
+
+## Task definition
+
+Given a divergence or fault scenario, the model must:
+
+- identify likely fault source  
+- determine isolation priority  
+- recommend reset or not  
+- define containment boundary  
+- estimate propagation risk  
+- output minimal stabilization plan  
+
+The objective is system coherence restoration.
+
+## Required outputs
+
+- suspected_fault_source  
+- isolation_priority  
+- reset_recommendation  
+- containment_boundary  
+- propagation_risk_score  
+- stabilization_confidence  
+- minimal_action_set  
+
+## Data structure
+
+Each row represents a fault scenario.
+
+### Key fields
+
+- scenario_id  
+- aircraft_phase  
+- subsystem_set  
+- divergence_summary  
+- fault_candidates  
+- isolation_options  
+- reset_options  
+- containment_actions  
+- propagation_risk  
+- optimal_strategy  
+- notes  
+- constraints  
+
+## Why this dataset matters
+
+Avionics redundancy protects aircraft only if faults are handled correctly.
+
+Key risks:
+- isolating the wrong unit  
+- resetting too early  
+- failing to contain drift  
+- losing redundancy  
+
+This dataset trains coherent response selection.
+
+It moves from:
+fault detection → controlled stabilization.
+
+## Evaluation
+
+Models are evaluated on:
+
+- correct fault source identification  
+- appropriate isolation choice  
+- reset decision accuracy  
+- containment completeness  
+- propagation risk estimation  
+
+Scoring includes:
+- classification accuracy  
+- action completeness  
+- reasoning integrity  
+
+## Use cases
+
+- automated fault containment  
+- redundancy management  
+- flight safety decision support  
+- avionics simulation  
+- resilience engineering  
+
+## Relationship to companion dataset
+
+This dataset follows:
+
+aviation-avionics-narrative-drift-and-divergence-detection
+
+That dataset detects divergence.  
+This dataset determines the response.
+
+Together they form a full loop:
+detect → contain → stabilize.
+
+## Limitations
+
+Structured benchmark format.  
+Not raw avionics logs.
+
+Future versions may include:
+- richer time-series  
+- larger scenario sets  
+- simulator-derived cases  
+
+Version: v0.1