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Move it through posed, modelled, configured, solved: What is the minimum total cost, and is the solution found optimal?\",\"role\":\"worker\",\"title\":\"Q1 is at stage 'posed' (1/8) of the optimization@2 workflow — no live artifact kind=instance part_of Q1. Move it through posed, modelled, configured, solved: What is the minimum total cost, and is the solution found optimal?\"}"},{"node":"a-80b52048c6aa8c82","v":2,"at":"2026-10-27T00:30:29+00:00","by":"solver","reason":"typed as instance","body":"{\"format\":\"csv\",\"kind\":\"instance\",\"path\":\"instance.csv\",\"sha256\":\"80b52048c6aa8c82872a7e9a841932fb1ac4f0911de8cab9e9402f3658cecf97\",\"size\":87.0}"},{"node":"n710d78e3b841","v":1,"at":"2026-10-27T00:30:30+00:00","by":"solver","reason":"","body":"{\"predictions\":[\"a feasible assignment exists and full enumeration finds the minimum with a bound equal to the objective\"],\"statement\":\"Assignment as a capacitated facility problem: each customer to one depot, depot capacities binding, cost = the sum of assignment costs.\"}"},{"node":"n47d05d97970d","v":1,"at":"2026-10-27T00:30:31+00:00","by":"solver","reason":"","body":"{\"aim\":\"Test H1 for Q1 from the files.\",\"protocol\":\"Enumerate every capacity-feasible assignment of the 6 customers to the 3 depots (3^6 candidates); the minimum is the optimum and its own bound.\",\"success_criteria\":\"the prediction holds in the files, as registered values\"}"},{"node":"n5e1ab77808a5","v":1,"at":"2026-10-27T00:30:32+00:00","by":"solver","reason":"","body":"{\"config\":{\"language\":\"python\",\"source\":\"import csv, itertools\\nrows = list(csv.reader(open('instance.csv')))\\ncost = [[int(x) for x in r[1:]] for r in rows[1:-1]]; cap = [int(x) for x in rows[-1][1:]]\\nbest, arg, n_feasible = None, None, 0\\nfor a in itertools.product(range(3), repeat=len(cost)):\\n    if any(a.count(d) > cap[d] for d in range(3)):\\n        continue\\n    n_feasible += 1\\n    c = sum(cost[i][d] for i, d in enumerate(a))\\n    if best is None or c < best:\\n        best, arg = c, a\\nprint('objective', best); print('feasible', 1); print('bound', best); print('gap', 0.0)\\nprint('enumerated_feasible', n_feasible); print('assignment', ''.join(map(str, arg)))\\n\"},\"kind\":\"agent\",\"name\":\"Q1 computation\",\"note\":\"import csv, itertools\\nrows = list(csv.reader(open('instance.csv')))\\ncost = [[int(x) for x in r[1:]] for r in rows[1:-1]]; cap = [int(x) for x in rows[-1][1:]]\\nbest, arg, n_feasible = None, None, 0\\nfor a in itertools.product(range(3), repeat=len(cost)):\\n    if any(a.count(d) > cap[d] for d in range(3)):\\n        continue\\n    n_feasible += 1\\n    c = sum(cost[i][d] for i, d in enumerate(a))\\n    if best is None or c < best:\\n        best, arg = c, a\\nprint('objective', best); print('feasible', 1); print('bound', best); print('gap', 0.0)\\nprint('enumerated_feasible', n_feasible); print('assignment', ''.join(map(str, arg)))\",\"state\":\"succeeded\"}"},{"node":"nf945134a0fba","v":1,"at":"2026-10-27T00:30:32+00:00","by":"solver","reason":"","body":"{\"kind\":\"computed\",\"summary\":\"Q1: Enumerated every capacity-feasible assignment (3^6 = 729 candidates) and kept the cheapest.\",\"values\":{\"bound\":{\"value\":20},\"enumerated_feasible\":{\"value\":210},\"feasible\":{\"value\":true},\"gap\":{\"value\":0.0},\"objective\":{\"value\":20}}}"},{"node":"n158332c1b079","v":1,"at":"2026-10-27T00:30:32+00:00","by":"solver","reason":"","body":"{\"measurements\":[{\"key\":\"bound\",\"name\":\"bound\",\"result\":\"nf945134a0fba\",\"value\":20}],\"scope\":\"instance.csv as given; capacities 2, 2, 3; full enumeration.\",\"statement\":\"The minimum total cost is 20, and the solution is optimal: the bound from full enumeration equals the objective.\"}"},{"node":"nc7cef3b8aa30","v":1,"at":"2026-10-27T00:30:33+00:00","by":"instrument","reason":"","body":"{\"config\":{\"confirmed\":[\"bound\",\"enumerated_feasible\",\"feasible\",\"gap\",\"objective\"],\"contradicted\":[],\"reproduces\":\"n5e1ab77808a5\",\"stdout_tail\":\"objective 20\\nfeasible 1\\nbound 20\\ngap 0.0\\nenumerated_feasible 210\\nassignment 011202\\n\",\"unprinted\":[]},\"kind\":\"lab\",\"name\":\"re-execution of RUN3\",\"note\":\"re-ran RUN3's registered code: 5 of 5 registered values confirmed by the output\",\"state\":\"succeeded\"}"},{"node":"n9ed75b886795","v":1,"at":"2026-10-27T00:30:33+00:00","by":"instrument","reason":"","body":"{\"kind\":\"computed\",\"outcome\":\"positive\",\"summary\":\"Re-executed RUN3's code: 5 of 5 registered values confirmed by the output.\",\"values\":{\"bound\":{\"value\":20},\"enumerated_feasible\":{\"value\":210},\"feasible\":{\"value\":true},\"gap\":{\"value\":0.0},\"objective\":{\"value\":20}}}"},{"node":"n8854b04c9fd6","v":1,"at":"2026-10-27T00:30:33+00:00","by":"harness","reason":"","body":"{\"choice\":\"Accept T2: Q1 is at stage 'posed' (1/8) of the optimization@2 workflow — no live artifact kind=instance part_of Q1. 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Review CL1, the claim that answers it: the order lists it, its values and what it rests on, and what the instrument's re-run confirmed — recompute only a value it CONTRADICTED; a value merely not printed is not evidence against. Judge th\"}"},{"node":"n761e047ccca4","v":1,"at":"2026-10-27T00:30:35+00:00","by":"verifier","reason":"","body":"{\"method\":\"Read the result's code and values; the claim says what the result says.\",\"notes\":\"Numbers hold; wording stays within the evidence.\",\"official\":true,\"verdict\":\"checked\"}"},{"node":"n1ef8c6d798ff","v":1,"at":"2026-10-27T00:30:36+00:00","by":"harness","reason":"","body":"{\"choice\":\"Accept T3: Q1 is at stage 'checked' (5/8) of the optimization@2 workflow. 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Review RS1, the result that answers it: the order lists it, its values and what it rests on, and what the instrument's re-run confirmed — recompute only a value it CONTRADICTED; a value merely not printed is not evidence against. Judge\"}"},{"node":"na1d98fea2ef7","v":1,"at":"2026-10-27T00:30:39+00:00","by":"verifier","reason":"","body":"{\"method\":\"Read the result's code and values; the claim says what the result says.\",\"notes\":\"Numbers hold; wording stays within the evidence.\",\"official\":true,\"verdict\":\"checked\"}"},{"node":"n90774b61c13c","v":1,"at":"2026-10-27T00:30:39+00:00","by":"harness","reason":"","body":"{\"choice\":\"Accept T4: Q1 is at stage 'verified' (5/8) of the optimization@2 workflow. 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Assign every customer to one depot without exceeding capacity, at minimum total cost. Report objective, feasibility and a bound or gap; say 'optimal' only with a bound that meets the objective.","claims":[{"id":"n158332c1b079","code":"CL1","type":"claim","title":"The minimum total cost is 20, and the solution is optimal: the bound from full enumeration equals the objective.","lifecycle":"active","review":"checked","verdicts":["verifier: checked (RV1, on v1)"],"v":1,"evidence":"project_rerun","lines":1,"stale":[]}],"results":[{"id":"nf945134a0fba","code":"RS1","type":"result","title":"Q1: Enumerated every capacity-feasible assignment (3^6 = 729 candidates) and kept the cheapest.","outcome":"unstated","by":"solver","in_a_claim":true,"lifecycle":"active","stale":[]},{"id":"n9ed75b886795","code":"RS2","type":"result","title":"Re-executed RUN3's code: 5 of 5 registered values confirmed by the output.","outcome":"positive","by":"instrument","in_a_claim":false,"lifecycle":"active","stale":[]}],"hypotheses":[{"id":"n710d78e3b841","code":"H1","type":"hypothesis","title":"Assignment as a capacitated facility problem: each customer to one depot, depot capacities binding, cost = the sum of assignment costs.","lifecycle":"active","support":0,"challenges":0}],"experiments":[{"id":"n47d05d97970d","code":"X1","type":"experiment","title":"Test H1 for Q1 from the files.","preregistered":true,"tests":["H1"],"executed":true,"lifecycle":"active"}],"open":{"claims_unreviewed":[],"claims_contested":[],"claims_stale":[],"results_in_no_claim":["RS2"],"experiments_not_preregistered":[]},"spend":{"usd":0.0,"calls":0,"reviews":2,"usd_per_verdict":null,"last_moved":"2026-10-27T00:30:41+00:00","metered":false},"seq":59,"workflow":{"profile":"optimization@2","report":"Solution report","method":"Operations-research practice: model before solving; a solution is only a solution if feasible; 'optimal' is a statement about a bound (the MIP gap convention); the solver's answer is verified against the instance by someone other than the modeller; a recommendation says how it moves with the data (Williams, Model Building in Mathematical Programming).","questions":[{"question":"nd635af7cc724","code":"Q1","profile":"optimization@2","workflow":true,"stage":"checked","index":7,"of":8,"complete":true,"next":"","gates":[{"stage":"posed","gate":"instance_registered","met":true,"optional":false,"why":"","evidence":["A1"],"who":"lead"},{"stage":"modelled","gate":"hypothesis_stated","met":true,"optional":false,"why":"","evidence":["H1"],"who":"modeller"},{"stage":"configured","gate":"preregistered","met":true,"optional":false,"why":"","evidence":["X1"],"who":"solver"},{"stage":"solved","gate":"solved","met":true,"optional":false,"why":"","evidence":["RS1"],"who":"solver, instrument"},{"stage":"verified","gate":"result_reviewed","met":true,"optional":false,"why":"","evidence":["RS1"],"who":"verifier"},{"stage":"claimed","gate":"claim_made","met":true,"optional":false,"why":"","evidence":["CL1"],"who":"solver"},{"stage":"checked","gate":"reviewed","met":true,"optional":false,"why":"","evidence":["CL1"],"who":"verifier"},{"stage":"recommended","gate":"decided","met":false,"optional":true,"why":"no decision is based on a claim or result on Q1","evidence":[],"who":"lead"}]}],"stale":[]},"markdown":"## Facts from the research graph — INV1 Assign six customers to three depots at minimum cost (active)\n_Generated from the record at event 59; do not edit — regenerate it from the graph. Interpretation goes below this section._\n\n### Claims\n\n| claim | standing | review | verdicts | statement |\n|---|---|---|---|---|\n| CL1 v1 | active | checked | verifier: checked (RV1, on v1) | The minimum total cost is 20, and the solution is optimal: the bound from full enumeration equals the objective. |\n\n### Results\n\n| result | outcome | by | carried by a claim | summary |\n|---|---|---|---|---|\n| RS1 | unstated | solver | yes | Q1: Enumerated every capacity-feasible assignment (3^6 = 729 candidates) and kept the cheapest. |\n| RS2 | positive | instrument | NO | Re-executed RUN3's code: 5 of 5 registered values confirmed by the output. |\n\n### Hypotheses\n\n- H1 (active; support lines 0, challenges 0): Assignment as a capacitated facility problem: each customer to one depot, depot capacities binding, cost = the sum of assignment costs.\n\n### Experiments\n\n- X1 tests H1: preregistered, run — Test H1 for Q1 from the files.\n\n### Workflow — Solution report (optimization@2)\n\n| question | stage | next gate |\n|---|---|---|\n| Q1 | checked (7/8) | complete |\n\nStale evidence (a file it used was superseded or withdrawn, its page changed, or valid_until passed): none\n\n### Open items\n\n- claims not yet reviewed: none\n- claims contested: none\n- claims on stale evidence (what they rest on has changed since; a check of them no longer counts): none\n- results no claim carries (their conclusions are unreviewed): RS2\n- experiments not preregistered: none"},"profile":{"id":"optimization@2","name":"optimization","version":2,"about":"An objective under constraints: a solution is a feasible incumbent with a bound or gap; 'optimal' needs the bound. 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