{"abstract":"Retrieval channel weights disappear during fusion.","category":"Vector retrieval ranking","checks":6,"contract":"Lists contain unique IDs in ranked order and have one corresponding positive integer weight each. Offset is a positive integer. Sum weight/(offset+one-based rank); missing IDs contribute zero. Return IDs by descending exact Fraction total then ID.","contract_signature":"lists, weights, offset","evaluation_group":"vector-retrieval-weighted-rank-fusion","failed_approach":"Applying the weight but starting at zero assigns an extra reciprocal contribution to the first-ranked item.","family":"w3-vector-retrieval-ranking-weighted-rank-fusion","id":"FA-99451","implementations":{"attempt":{"sha256":"e8308b67883a735806780f0d28dddb54a2a8180c84ec67711a5a6c6e46ddedf4","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(lists, weights, offset):\n    from fractions import Fraction\n    s={}\n    for xs,w in zip(lists,weights):\n     for rank,(ident,score) in enumerate(xs): s[ident]=s.get(ident,0)+Fraction(w,offset+rank)\n    return sorted(s,key=lambda x:(-s[x],x))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('trusted channel weight',solve([[['a',9],['x',0]],[['b',8],['x',0]]],[5,1],1),['a','x','b'])\ncheck('weight reverses winner',solve([[['a',1]],[['b',1]]],[1,4],2),['b','a'])\ncheck('missing candidate contribution',solve([[['a',1],['x',0]],[['b',1],['x',0]]],[3,2],1),['x','a','b'])\ncheck('deep rank weighted',solve([[['a',1],['b',0],['x',0]],[['b',1]]],[1,4],1),['b','a','x'])\ncheck('one list weight',solve([[['z',0],['a',0]]],[N+2],N),['z','a'])\ncheck('several unequal weights',solve([[['a',1],['b',0]],[['c',1],['b',0]]],[N+1,2],N),['b','a','c'])\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":"692f467371588a36cde09d7a0b2eaf0eec5bce4563c0d09218bc890acc16c4c5","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(lists, weights, offset):\n    from fractions import Fraction\n    s={}\n    for xs in lists:\n     for rank,(ident,score) in enumerate(xs,1): s[ident]=s.get(ident,0)+Fraction(1,offset+rank)\n    return sorted(s,key=lambda x:(-s[x],x))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('trusted channel weight',solve([[['a',9],['x',0]],[['b',8],['x',0]]],[5,1],1),['a','x','b'])\ncheck('weight reverses winner',solve([[['a',1]],[['b',1]]],[1,4],2),['b','a'])\ncheck('missing candidate contribution',solve([[['a',1],['x',0]],[['b',1],['x',0]]],[3,2],1),['x','a','b'])\ncheck('deep rank weighted',solve([[['a',1],['b',0],['x',0]],[['b',1]]],[1,4],1),['b','a','x'])\ncheck('one list weight',solve([[['z',0],['a',0]]],[N+2],N),['z','a'])\ncheck('several unequal weights',solve([[['a',1],['b',0]],[['c',1],['b',0]]],[N+1,2],N),['b','a','c'])\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 small exact toy vectors and scores. No production index, ANN recall, embedding quality, or latency claim is implied. 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-vector-retrieval-ranking-weighted-rank-fusion","generated_at":"2026-09-30T16:48:24.475676+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"An offline vector retrieval toy model isolates one ranking contract from embedding generation, storage, and serving.","root_cause":"Each channel contributes the same reciprocal-rank value regardless of its configured reliability weight.","sha256":"e5c8607a784be95d7f873613826dab12dbee6109d733fd90f6f0f7d29f14446c","title":"Vector retrieval: Retrieval channel weights disappear during fusion · 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":28.392,"exit_code":1,"observations":[{"actual":["a","x","b"],"check":"trusted channel weight","expected":["a","x","b"],"passed":true},{"actual":["b","a"],"check":"weight reverses winner","expected":["b","a"],"passed":true},{"actual":["a","x","b"],"check":"missing candidate contribution","expected":["x","a","b"],"passed":false},{"actual":["b","a","x"],"check":"deep rank weighted","expected":["b","a","x"],"passed":true},{"actual":["z","a"],"check":"one list weight","expected":["z","a"],"passed":true},{"actual":["a","b","c"],"check":"several unequal weights","expected":["b","a","c"],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"trusted channel weight\", \"actual\": [\"a\", \"x\", \"b\"], \"expected\": [\"a\", \"x\", \"b\"], \"passed\": true}, {\"check\": \"weight reverses winner\", \"actual\": [\"b\", \"a\"], \"expected\": [\"b\", \"a\"], \"passed\": true}, {\"check\": \"missing candidate contribution\", \"actual\": [\"a\", \"x\", \"b\"], \"expected\": [\"x\", \"a\", \"b\"], \"passed\": false}, {\"check\": \"deep rank weighted\", \"actual\": [\"b\", \"a\", \"x\"], \"expected\": [\"b\", \"a\", \"x\"], \"passed\": true}, {\"check\": \"one list weight\", \"actual\": [\"z\", \"a\"], \"expected\": [\"z\", \"a\"], \"passed\": true}, {\"check\": \"several unequal weights\", \"actual\": [\"a\", \"b\", \"c\"], \"expected\": [\"b\", \"a\", \"c\"], \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":30.391,"exit_code":1,"observations":[{"actual":["x","a","b"],"check":"trusted channel weight","expected":["a","x","b"],"passed":false},{"actual":["a","b"],"check":"weight reverses winner","expected":["b","a"],"passed":false},{"actual":["x","a","b"],"check":"missing candidate contribution","expected":["x","a","b"],"passed":true},{"actual":["b","a","x"],"check":"deep rank weighted","expected":["b","a","x"],"passed":true},{"actual":["z","a"],"check":"one list weight","expected":["z","a"],"passed":true},{"actual":["b","a","c"],"check":"several unequal weights","expected":["b","a","c"],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"trusted channel weight\", \"actual\": [\"x\", \"a\", \"b\"], \"expected\": [\"a\", \"x\", \"b\"], \"passed\": false}, {\"check\": \"weight reverses winner\", \"actual\": [\"a\", \"b\"], \"expected\": [\"b\", \"a\"], \"passed\": false}, {\"check\": \"missing candidate contribution\", \"actual\": [\"x\", \"a\", \"b\"], \"expected\": [\"x\", \"a\", \"b\"], \"passed\": true}, {\"check\": \"deep rank weighted\", \"actual\": [\"b\", \"a\", \"x\"], \"expected\": [\"b\", \"a\", \"x\"], \"passed\": true}, {\"check\": \"one list weight\", \"actual\": [\"z\", \"a\"], \"expected\": [\"z\", \"a\"], \"passed\": true}, {\"check\": \"several unequal weights\", \"actual\": [\"b\", \"a\", \"c\"], \"expected\": [\"b\", \"a\", \"c\"], \"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."}}