{"id":"W4398270065","doi":"10.7910/dvn/ii5jzg","title":"Randomly generated problems for the complexity resolution problem in a multi sector planning context","year":2020,"lang":"en","type":"dataset","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Context (archaeology); Resolution (logic); Computer science; Artificial intelligence; Geography; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007943991,0.0006805653,0.0007968697,0.000445985,0.0002952812,0.0003217694,0.0007513171,0.0007091603,0.00004200668],"category_scores_gemma":[0.0002009808,0.0005997593,0.0002315636,0.0007568353,0.0001326166,0.0001799153,0.0001346389,0.001214206,0.00002603502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005372537,"about_ca_system_score_gemma":0.0001893252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005616546,"about_ca_topic_score_gemma":0.01452331,"domain_scores_codex":[0.9971434,0.0001830165,0.0009468384,0.0005677789,0.0003123717,0.0008466229],"domain_scores_gemma":[0.9983402,0.0002858822,0.0002970846,0.0007171145,0.0001391096,0.000220598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001119655,0.00005090801,0.00004708269,0.0003761883,0.00008328626,0.000008419386,0.0001830173,0.4403498,0.0001082674,0.0001332775,0.5582908,0.0002569666],"study_design_scores_gemma":[0.001802363,0.00005789697,0.00009112513,0.0002503008,0.00005215485,0.00001380143,0.00002641093,0.5687955,0.00008708847,0.0000916412,0.428304,0.0004277171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.00001180804,0.002877801,0.5120012,0.001016598,0.0002784804,0.003865765,0.479111,0.0008139501,0.00002335866],"genre_scores_gemma":[0.002507905,0.001351599,0.07451728,0.001884899,0.0003698852,0.006423133,0.9124411,0.0002772389,0.0002269655],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4374839,"threshold_uncertainty_score":0.9996454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05106732303624932,"score_gpt":0.2545901354405072,"score_spread":0.2035228124042579,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}