{"abstract":"Augmented copies receive the base weight instead of divided weight.","category":"Training label alignment","checks":7,"contract":"Rows are [label,weight,view_count]. Return one [label,weight/view_count] row per view; nonpositive view counts emit nothing.","contract_signature":"rows","evaluation_group":"training-label-alignment-conserved-augmentation-weight","failed_approach":"Applying the full weight only to the first view conserves weight but discards supervision from the other views.","family":"w3-training-label-alignment-weighted-target-expansion","id":"FA-98021","implementations":{"attempt":{"sha256":"0e7ec63a3f47cbeea94edb7738b1c5c7b9948cc9169e0de2eb46d13585258092","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(rows):\n    return [[y,w] for y,w,count in rows for i in range(count) if i==0]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('weight conserved across views',solve([[N,6,N]]),[[N,6/N]]*N)\ncheck('one view unchanged',solve([['x',4,1]]),[['x',4.0]])\ncheck('zero views',solve([['x',4,0]]),[])\ncheck('empty batch',solve([]),[])\ncheck('multiple sources',solve([['a',8,2],['b',3,1]]),[['a',4.0],['a',4.0],['b',3.0]])\ncheck('fractional share',solve([['c',1,4]]),[['c',0.25]]*4)\ncheck('negative weight preserved',solve([['d',-6,3]]),[['d',-2.0]]*3)\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":"a2a8193648f8f5bdbcd51058bc23ef5325eeefd51bbaace00b3d491d38e982af","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(rows):\n    return [[y,w] for y,w,count in rows for _ in range(count)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('weight conserved across views',solve([[N,6,N]]),[[N,6/N]]*N)\ncheck('one view unchanged',solve([['x',4,1]]),[['x',4.0]])\ncheck('zero views',solve([['x',4,0]]),[])\ncheck('empty batch',solve([]),[])\ncheck('multiple sources',solve([['a',8,2],['b',3,1]]),[['a',4.0],['a',4.0],['b',3.0]])\ncheck('fractional share',solve([['c',1,4]]),[['c',0.25]]*4)\ncheck('negative weight preserved',solve([['d',-6,3]]),[['d',-2.0]]*3)\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":"Weights are finite numbers; view_count is a nonnegative integer. 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-training-label-alignment-weighted-target-expansion","generated_at":"2026-09-30T16:48:08.406736+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A small deterministic training-data operation makes label ownership and ordering explicit.","root_cause":"Each source example is duplicated into several views without conserving its total training weight.","sha256":"03b765fab52f0ba804bde4a2a0a23c1bd86f05480377b475900e4bc7967448fd","title":"Augmented copies receive the base weight instead of divided weight · 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":26.595,"exit_code":1,"observations":[{"actual":[[1,6]],"check":"weight conserved across views","expected":[[1,6.0]],"passed":true},{"actual":[["x",4]],"check":"one view unchanged","expected":[["x",4.0]],"passed":true},{"actual":[],"check":"zero views","expected":[],"passed":true},{"actual":[],"check":"empty batch","expected":[],"passed":true},{"actual":[["a",8],["b",3]],"check":"multiple sources","expected":[["a",4.0],["a",4.0],["b",3.0]],"passed":false},{"actual":[["c",1]],"check":"fractional share","expected":[["c",0.25],["c",0.25],["c",0.25],["c",0.25]],"passed":false},{"actual":[["d",-6]],"check":"negative weight preserved","expected":[["d",-2.0],["d",-2.0],["d",-2.0]],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"weight conserved across views\", \"actual\": [[1, 6]], \"expected\": [[1, 6.0]], \"passed\": true}, {\"check\": \"one view unchanged\", \"actual\": [[\"x\", 4]], \"expected\": [[\"x\", 4.0]], \"passed\": true}, {\"check\": \"zero views\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty batch\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"multiple sources\", \"actual\": [[\"a\", 8], [\"b\", 3]], \"expected\": [[\"a\", 4.0], [\"a\", 4.0], [\"b\", 3.0]], \"passed\": false}, {\"check\": \"fractional share\", \"actual\": [[\"c\", 1]], \"expected\": [[\"c\", 0.25], [\"c\", 0.25], [\"c\", 0.25], [\"c\", 0.25]], \"passed\": false}, {\"check\": \"negative weight preserved\", \"actual\": [[\"d\", -6]], \"expected\": [[\"d\", -2.0], [\"d\", -2.0], [\"d\", -2.0]], \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":26.565,"exit_code":1,"observations":[{"actual":[[1,6]],"check":"weight conserved across views","expected":[[1,6.0]],"passed":true},{"actual":[["x",4]],"check":"one view unchanged","expected":[["x",4.0]],"passed":true},{"actual":[],"check":"zero views","expected":[],"passed":true},{"actual":[],"check":"empty batch","expected":[],"passed":true},{"actual":[["a",8],["a",8],["b",3]],"check":"multiple sources","expected":[["a",4.0],["a",4.0],["b",3.0]],"passed":false},{"actual":[["c",1],["c",1],["c",1],["c",1]],"check":"fractional share","expected":[["c",0.25],["c",0.25],["c",0.25],["c",0.25]],"passed":false},{"actual":[["d",-6],["d",-6],["d",-6]],"check":"negative weight preserved","expected":[["d",-2.0],["d",-2.0],["d",-2.0]],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"weight conserved across views\", \"actual\": [[1, 6]], \"expected\": [[1, 6.0]], \"passed\": true}, {\"check\": \"one view unchanged\", \"actual\": [[\"x\", 4]], \"expected\": [[\"x\", 4.0]], \"passed\": true}, {\"check\": \"zero views\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty batch\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"multiple sources\", \"actual\": [[\"a\", 8], [\"a\", 8], [\"b\", 3]], \"expected\": [[\"a\", 4.0], [\"a\", 4.0], [\"b\", 3.0]], \"passed\": false}, {\"check\": \"fractional share\", \"actual\": [[\"c\", 1], [\"c\", 1], [\"c\", 1], [\"c\", 1]], \"expected\": [[\"c\", 0.25], [\"c\", 0.25], [\"c\", 0.25], [\"c\", 0.25]], \"passed\": false}, {\"check\": \"negative weight preserved\", \"actual\": [[\"d\", -6], [\"d\", -6], [\"d\", -6]], \"expected\": [[\"d\", -2.0], [\"d\", -2.0], [\"d\", -2.0]], \"passed\": false}], \"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."}}