{"slug":"oip-node-c15-optimization-under-constraint-pareto-fronts","verification":{"valid":true,"entries":5,"head":"d9096bf3fd51862de31e05dec29f4a31053c13cfa36b3ac631683ec5f2a9f9a9"},"energy":{"passes":5,"tokens_in":3404,"tokens_out":2261,"tokens_total":5665,"cost_usd":0,"models":{"claude-fable-5":2,"grok/grok-4.3":1,"scorer":1,"owner":1},"head":"d9096bf3fd51862de31e05dec29f4a31053c13cfa36b3ac631683ec5f2a9f9a9"},"provenance":[{"ts":"2026-07-04T04:34:05.456Z","model":"claude-fable-5","action":"edit","prompt":"","input":"","response":"","tokens_in":0,"tokens_out":0,"cost":0,"prev":"genesis","hash":"b0c378579795f0fb33706d49e3f04e82c86fbaa99505e1fbeeb39a88d04b62f6"},{"ts":"2026-07-04T05:02:02.274Z","model":"claude-fable-5","action":"edit","prompt":"","input":"","response":"","tokens_in":0,"tokens_out":0,"cost":0,"prev":"b0c378579795f0fb33706d49e3f04e82c86fbaa99505e1fbeeb39a88d04b62f6","hash":"a8d64e7d8cc8a58d5df3fb03d1d6c68136e369fd77f4130af903b5e531e842b7"},{"ts":"2026-07-07T07:55:52.926Z","model":"grok/grok-4.3","action":"atomize","prompt":"You are the claim atomizer for the miscsubjects.com philosophy and OIP corpus. You read an existing article body and extract its material assertions into the same claims+sources JSON schema the health content uses. The body is read-only input.\n\nALWAYS:\n- Extract every material assertion as one atomic claim, tied to the ## section it came from.\n- Tier honestly: human = empirically established; mechanistic = formally proven or mathematical; anecdotal = historical or textual attribution; speculative = metaphysical or interpretive.\n- Attach real sources (primary works, papers, books) with exact quotes only where you can verify them; otherwise mark the claim unsourced.\n- Prefer fewer, harder claims over many soft ones.\n\nNEVER:\n- Never rewrite, summarize, or output the body.\n- Never invent a URL, quote, or publication.\n- Never duplicate an existing claim text.","input":"atomize oip-node-c15-optimization-under-constraint-pareto-fronts","response":"{\n  \"claims\": [\n    {\n      \"id\": \"c1\",\n      \"text\": \"Systems settle at states where no objective can improve without another worsening; Pareto optimality and thermodynamic bounds define the feasible frontier of natural and designed systems.\",\n      \"section\": \"# Node C15: Optimization Under Constraint / Pareto Fronts\",\n      \"tier\": \"mechanistic\",\n      \"source_ids\": [],\n      \"source_status\": \"unsourced\",\n      \"why_material\": \"Core definition of the optimization constraint pattern across domains.\"\n    },\n    {\n      \"id\": \"c2\",\n      \"text\": \"A solution dominates another if it is better on at least one objective and not worse on any; the Pareto front is the set of non-dominated solutions.\",\n      \"section\": \"# Node C15: Optimization Under Constraint / Pareto Fronts\",\n      \"tier\": \"mechanistic\",\n      \"source_ids\": [],\n      \"source_status\": \"unsourced\",\n      \"why_material\": \"Formal definition of Pareto dominance and front.\"\n    },\n    {\n      \"id\": \"c3\",\n      \"text\": \"Carnot efficiency sets the maximum work extractable between two reservoirs.\",\n      \"section\": \"# Node C15: Optimization Under Constraint / Pareto Fronts\",\n      \"tier\": \"mechanistic\",\n      \"source_ids\": [],\n      \"source_status\": \"unsourced\",\n      \"why_material\": \"Thermodynamic bound as example of constraint.\"\n    },\n    {\n      \"id\": \"c4\",\n      \"text\": \"Life-history trade-offs (growth vs. reproduction) reflect allocation constraints.\",\n      \"section\": \"# Node C15: Optimization Under Constraint / Pareto Fronts\",\n      \"tier\": \"mechanistic\",\n      \"source_ids\": [],\n      \"source_status\": \"unsourced\",\n      \"why_material\": \"Biological application of trade-off under constraint.\"\n    },\n    {\n      \"id\": \"c5\",\n      \"text\": \"pattern_type is mathematical and maps_to_axiom includes A2 and A3.\",\n      \"section\": \"# Node C15: Optimization Under Constraint / Pareto Fronts\",\n      \"tier\": \"mechanistic\",\n      \"source_ids\": [],\n      \"source_status\": \"unsourced\",\n      \"why_material\": \"Classification ","tokens_in":3404,"tokens_out":2261,"cost":0,"prev":"a8d64e7d8cc8a58d5df3fb03d1d6c68136e369fd77f4130af903b5e531e842b7","hash":"8f773c1ac56e62444a4fbda26b465f4dbce29e4004c2c7049dcc98b9b8ded315"},{"ts":"2026-07-07T07:55:53.242Z","model":"scorer","action":"score","prompt":"","input":"oip-node-c15-optimization-under-constraint-pareto-fronts","response":"[]","tokens_in":0,"tokens_out":0,"cost":0,"prev":"8f773c1ac56e62444a4fbda26b465f4dbce29e4004c2c7049dcc98b9b8ded315","hash":"db879c5441661d857a9df0b0b60db10052aa1f7f3169a971b4f6723294290ac9"},{"ts":"2026-07-17T02:36:21.450Z","model":"owner","action":"voxel_divide","prompt":"","input":"oip-node-c15-optimization-under-constraint-pareto-fronts","response":"5 DIVs from body (verbatim, roundtrip-checked)","tokens_in":0,"tokens_out":0,"cost":0,"prev":"db879c5441661d857a9df0b0b60db10052aa1f7f3169a971b4f6723294290ac9","hash":"d9096bf3fd51862de31e05dec29f4a31053c13cfa36b3ac631683ec5f2a9f9a9"}]}