Comprehension accuracy (Δ)

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{
    "construct": "impact-recovered(<impact-check>@<t>) / cause-resolved(<cause-ref>, checked-by=<test-ref>) - two independent, composable incident-repair claims; bare 'fixed' refused where the next action depends on which axis holds",
    "metric": "comprehension_accuracy_delta",
    "seed": 20260919,
    "comparator": {
        "kind": "complete-careful-english-v1",
        "description": "The identical frozen workflow policy and incident file, with each asserted claim written in the proposal's own declared careful-English mapping instead of the registered notation: 'The named <incident> impact was absent under <check> at <t>.' and 'the <cause> cause was removed and the post-change <test> test passed.'"
    },
    "study_purpose": "claim_test",
    "study_scope": "CLAIM-CARRIER ORIGINAL (impact-recovered / cause-resolved). 192 fresh handoffs = 4 assertion cells x 48 (impact only / cause only / both / neither); physical truth crossed 2x2 and recorded NOWHERE in the message (references only); 6 domains x 8. TWO held-out consequence questions per handoff, each its own stratum: Q1 exact assertion recovery, Q2 routing under the frozen policy printed identically in both arms. 384 real items x 1 reader, arm-forced 24/24 per (cell, question); every handoff is read in BOTH renderings. English arm = the proposal's own declared english_mapping applied to fresh incidents; options use vocabulary held out of both arms. The neither-claim cell carries the same assertion in both arms (no marker exists to render): declared contrast-free by construction, weighted like the others, reported as the over-inference diagnostic. Fresh ids/refs/domains/times; 0 case-specific 8-gram overlap; keys re-derived by two parsers, 0 defects. Filed unchanged.",
    "items_sha256": "c9e218fd613c70d52e055536dc844c5904812f52dd03f07927cfa34e16d9ae82",
    "items_url": "https://x0.at/MP4k.json",
    "models": [
        "deepseek-flash-minimal"
    ],
    "admissibility": {
        "kind": "ainglish.panel.admissibility.v1",
        "per_reader_calibration": true,
        "max_absent_cells": 6,
        "max_off_option_cells": 0,
        "max_transport_fault_cells": 6,
        "max_truncated_cells": 0
    },
    "readers": [
        {
            "name": "deepseek-flash-minimal",
            "provider": "openai-compatible",
            "model": "deepseek-flash",
            "api": "openai",
            "base_url": "https://api.deepseek.com/v1",
            "model_digest": null,
            "digest_source": "provider-opaque",
            "instrument_preparation": {
                "entry_point": "prepare_reader_instruments",
                "binding": "provider-opaque"
            },
            "answer_protocol": "opaque-choice-v1",
            "max_tokens": 32768,
            "timeout_s": 600,
            "temperature": null,
            "seed": "provider-default",
            "top_p": "provider-default",
            "top_k": "provider-default",
            "num_ctx": "provider-default",
            "reasoning_effort": "minimal"
        }
    ],
    "instrument_preparation": {
        "entry_point": "prepare_reader_instruments",
        "binding": [
            {
                "reader": "deepseek-flash-minimal",
                "digest_source": "provider-opaque"
            }
        ]
    },
    "item_counts": {
        "real": 384,
        "calibration": 12
    },
    "interval_kind": "bootstrap_items",
    "interval_estimator": {
        "kind": "ainglish.panel.bootstrap-items-attestation.v1",
        "algorithm": "sha256-counter-modulo-v1",
        "draws": 2000,
        "sampling_unit": "item",
        "quantiles": [
            "0.025",
            "0.975"
        ],
        "items_index_sha256": "494257bb6ce6dbbe14d0666e1f07395dde2e73cabb72c72640cbf0853b486534"
    },
    "settlement_strata": [
        {
            "id": "impact-only::assertion",
            "weight": 1
        },
        {
            "id": "impact-only::routing",
            "weight": 1
        },
        {
            "id": "cause-only::assertion",
            "weight": 1
        },
        {
            "id": "cause-only::routing",
            "weight": 1
        },
        {
            "id": "both-claims::assertion",
            "weight": 1
        },
        {
            "id": "both-claims::routing",
            "weight": 1
        },
        {
            "id": "neither-claim::assertion",
            "weight": 1
        },
        {
            "id": "neither-claim::routing",
            "weight": 1
        }
    ],
    "settlement_item_field": "settlement_stratum",
    "settlement_rule": "manifest-weighted arms and value; every stratum load-bearing",
    "calibration": {
        "planted_arm": "ainglish",
        "min_gap": 0.5,
        "min_recovered": 0.875,
        "rule": "headroom-relative-v1",
        "ordering": "calibration-first",
        "arm_exposure": "both-arms-per-reader-item",
        "cells": 24
    },
    "difficulty": {
        "annotated": false
    },
    "harness": "ainglish-panel/0.2.58",
    "transport": {
        "deepseek-flash-minimal": {
            "max_tokens": 32768,
            "timeout_s": 600,
            "temperature": null,
            "seed": "provider-default",
            "top_p": "provider-default",
            "top_k": "provider-default",
            "num_ctx": "provider-default",
            "reasoning_effort": "minimal"
        }
    },
    "concurrency": {
        "max_in_flight": 4,
        "per_reader_max_in_flight": {
            "deepseek-flash-minimal": 4
        },
        "result_order": "deterministic-plan-order",
        "calibration_barrier": true,
        "automatic_retries": false
    },
    "transport_faults": {
        "total": 0,
        "retried": false,
        "per_cell": []
    },
    "transport_truncations": {
        "total": 0,
        "per_reader_cell": [],
        "by_cell": {
            "english": 0,
            "ainglish": 0
        },
        "imbalanced_across_cells": false
    },
    "protocol": "panel.py counterbalanced real arms + both-arms-per-reader-item planted-effect calibration gate"
}