{"id":"W4254850371","doi":"10.1515/iupac.81.0487","title":"Interference Competition","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Computer science; Ecology; Risk assessment; Biology; Linguistics; Philosophy","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":[],"category_scores_codex":[0.0005077613,0.0003272195,0.0008404084,0.0005124114,0.0000954492,0.00009487681,0.0004929002,0.0002464958,0.06831235],"category_scores_gemma":[0.0002076921,0.0003138565,0.0003131867,0.0002507803,0.00009564103,0.0001128674,0.0001289267,0.0003199383,0.0002042403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156417,"about_ca_system_score_gemma":0.00009590865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000199863,"about_ca_topic_score_gemma":0.0005060009,"domain_scores_codex":[0.9980036,0.00003209632,0.0008830422,0.0006181915,0.0001459851,0.0003170909],"domain_scores_gemma":[0.9982742,0.00004122951,0.0005585657,0.0008041194,0.0001794006,0.0001425069],"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":[0.00002394918,0.0001267964,0.00004572766,0.00005706124,0.0001182882,0.000009022449,0.000006257493,8.82847e-7,6.941845e-7,0.01047968,0.9887759,0.0003557304],"study_design_scores_gemma":[0.0004038003,0.0000784778,0.00006135242,0.0001733744,0.00003032664,0.000003855882,0.00001052558,0.00002387977,0.000002680764,0.008312902,0.9904924,0.0004064323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000278091,0.001163671,0.006343231,0.0008352323,0.0009668849,0.0001053427,0.9883975,0.00004880574,0.002111558],"genre_scores_gemma":[0.0006230056,0.002608181,0.0000325956,0.000509541,0.0005604037,0.00001626484,0.9941279,0.00002514981,0.001496909],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06810812,"threshold_uncertainty_score":0.9999313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02486167773955355,"score_gpt":0.3360436401985673,"score_spread":0.3111819624590137,"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."}}