{"id":"W4398318671","doi":"10.7910/dvn/ii5jzg/a3voh8","title":"MSP_F_70_NFL_4_47.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; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001244552,0.004763247,0.002587726,0.00477033,0.001287858,0.004535981,0.005591767,0.004416072,0.2826805],"category_scores_gemma":[0.009600308,0.001416846,0.002156048,0.008634209,0.0009639435,0.002915359,0.003141339,0.002564385,0.3238919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002317961,"about_ca_system_score_gemma":0.002696716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01893914,"about_ca_topic_score_gemma":0.02704496,"domain_scores_codex":[0.9986254,0.000191585,0.0001393882,0.000375378,0.0003657828,0.0003024253],"domain_scores_gemma":[0.9969916,0.001079105,0.0002226213,0.0007750968,0.0006454343,0.0002860854],"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":[0.00003648406,0.00002419567,0.0002549196,0.0006888773,0.00001838913,0.0000107913,0.00001341466,0.0003345752,0.00005484715,0.0003615652,0.9968204,0.0013815],"study_design_scores_gemma":[0.0005708589,0.00004169367,0.001936216,0.0004125087,0.00002868922,0.00007577326,0.00008927879,0.001044692,0.000612943,0.002911382,0.9922323,0.00004363746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001063865,0.00008747773,0.00006981446,0.0000751808,0.00002812784,0.000009683608,0.9977324,0.0008869762,0.001003914],"genre_scores_gemma":[0.0004731238,0.0000992353,0.0003455719,0.00007259192,0.00001352386,0.00008014055,0.9979164,0.0002404729,0.0007588355],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7173195,"threshold_uncertainty_score":0.9456603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453785021965989,"score_gpt":0.2085162319873152,"score_spread":0.1939783817676553,"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."}}