{"abstract":"Macro recall weights labels by support.","category":"Evaluation metric aggregation","checks":6,"contract":"Average per-label recall over the supplied labels; a label with no actual examples has recall 0; empty label list returns 0.","contract_signature":"truth, pred, labels","evaluation_group":"w3-eval-macro-recall","failed_approach":"Including absent labels as zero changes the explicitly requested label set.","family":"w3-evaluation-metric-aggregation-macro-recall","id":"FA-99951","implementations":{"attempt":{"sha256":"b7acf85d2f849dcfb206243ee2a04c3841d381be832641f751b2d237ba9ee7a0","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(truth, pred, labels):\n    return sum(sum(a==k and b==k for a,b in zip(truth,pred))/sum(a==k for a in truth) if sum(a==k for a in truth) else 0 for k in labels+[99])/len(labels+[99]) if labels else 0\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('unequal supports',solve([0,0,0,1],[0,0,1,1],[0,1]),(2/3+1)/2)\ncheck('perfect',solve([0,1],[0,1],[0,1]),1)\ncheck('absent requested label',solve([0],[0],[0,1]),.5)\ncheck('empty labels',solve([0],[0],[]),0)\ncheck('empty data',solve([],[],[0,1]),0)\ncheck('all missed',solve([N]*N,[0]*N,[N]),0)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"19468ae21d0a8fc50ac823f07d527560df3bcb68e71ea8f618c211aeeee122df","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(truth, pred, labels):\n    return sum(sum(a==k and b==k for a,b in zip(truth,pred))/sum(a==k for a in truth) if sum(a==k for a in truth) else 0 for k in labels)/len(truth) if truth else 0\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('unequal supports',solve([0,0,0,1],[0,0,1,1],[0,1]),(2/3+1)/2)\ncheck('perfect',solve([0,1],[0,1],[0,1]),1)\ncheck('absent requested label',solve([0],[0],[0,1]),.5)\ncheck('empty labels',solve([0],[0],[]),0)\ncheck('empty data',solve([],[],[0,1]),0)\ncheck('all missed',solve([N]*N,[0]*N,[N]),0)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Inputs are finite toy labels and scores; this defines no benchmark protocol, production metric library, or model quality claim. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w3-evaluation-metric-aggregation-macro-recall","generated_at":"2026-09-30T16:48:29.887515+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A small explicit evaluation contract makes aggregation behavior reproducible across labeled examples.","root_cause":"Recall values are pooled through their counts, giving common labels extra weight.","sha256":"03d4143ffc9590389af19339540ae92711308991309b9ecbdc35b44703d317f4","title":"Macro recall weights labels by support · case 01","variant":1,"variant_policy":"The fixture code references N, supplied as 1 through 5. Fixed boundary checks may repeat. These records share one mechanism and must remain together in evaluation splits.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":31.167,"exit_code":1,"observations":[{"actual":0.5555555555555555,"check":"unequal supports","expected":0.8333333333333333,"passed":false},{"actual":0.6666666666666666,"check":"perfect","expected":1,"passed":false},{"actual":0.3333333333333333,"check":"absent requested label","expected":0.5,"passed":false},{"actual":0,"check":"empty labels","expected":0,"passed":true},{"actual":0.0,"check":"empty data","expected":0,"passed":true},{"actual":0.0,"check":"all missed","expected":0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"unequal supports\", \"actual\": 0.5555555555555555, \"expected\": 0.8333333333333333, \"passed\": false}, {\"check\": \"perfect\", \"actual\": 0.6666666666666666, \"expected\": 1, \"passed\": false}, {\"check\": \"absent requested label\", \"actual\": 0.3333333333333333, \"expected\": 0.5, \"passed\": false}, {\"check\": \"empty labels\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"empty data\", \"actual\": 0.0, \"expected\": 0, \"passed\": true}, {\"check\": \"all missed\", \"actual\": 0.0, \"expected\": 0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":29.622,"exit_code":1,"observations":[{"actual":0.41666666666666663,"check":"unequal supports","expected":0.8333333333333333,"passed":false},{"actual":1.0,"check":"perfect","expected":1,"passed":true},{"actual":1.0,"check":"absent requested label","expected":0.5,"passed":false},{"actual":0.0,"check":"empty labels","expected":0,"passed":true},{"actual":0,"check":"empty data","expected":0,"passed":true},{"actual":0.0,"check":"all missed","expected":0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"unequal supports\", \"actual\": 0.41666666666666663, \"expected\": 0.8333333333333333, \"passed\": false}, {\"check\": \"perfect\", \"actual\": 1.0, \"expected\": 1, \"passed\": true}, {\"check\": \"absent requested label\", \"actual\": 1.0, \"expected\": 0.5, \"passed\": false}, {\"check\": \"empty labels\", \"actual\": 0.0, \"expected\": 0, \"passed\": true}, {\"check\": \"empty data\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"all missed\", \"actual\": 0.0, \"expected\": 0, \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}