{"id":"W4398291406","doi":"10.7910/dvn/ii5jzg/hcc2q5","title":"MSP_F_100_NFL_4_22.xlsx","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","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; History; Artificial intelligence; 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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007884229,0.0003417257,0.0003293958,0.0001227718,0.00005321795,0.0001276444,0.0005392875,0.0002894818,0.02260533],"category_scores_gemma":[0.00006044439,0.0003739629,0.00008997649,0.0002183687,0.00003514813,0.0001630084,0.0001591034,0.0005006836,0.4070913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005306961,"about_ca_system_score_gemma":0.00004025832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002606043,"about_ca_topic_score_gemma":0.00002763617,"domain_scores_codex":[0.9988599,0.00002841442,0.0002919547,0.0003111143,0.0002419033,0.0002667037],"domain_scores_gemma":[0.9988612,0.00003199564,0.00005818541,0.0008239549,0.0000298058,0.0001948851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004428962,0.00001015359,7.023836e-7,0.0002945769,0.00007127228,0.00004994117,0.00001244002,0.007673122,0.000005578621,0.00001656887,0.99173,0.0001311831],"study_design_scores_gemma":[0.000240775,0.00001486308,0.000001210116,0.00006187956,0.00006962998,0.00000785119,0.000008493158,0.002905113,0.00001542888,0.00000697919,0.9962605,0.0004072301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[2.033582e-7,0.000002149652,0.0006424193,0.000005367794,0.001393679,0.0001757861,0.9957357,0.0004657219,0.001578959],"genre_scores_gemma":[0.000004131432,0.0008293906,0.0008026234,0.0003630105,0.0003300284,0.00001612633,0.9974217,0.00005865014,0.0001743722],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.384486,"threshold_uncertainty_score":0.9998713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407897303491542,"score_gpt":0.2087701466747898,"score_spread":0.1946911736398744,"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."}}