{"id":"W4230685860","doi":"10.1515/iupac.83.0328","title":"Antagonist","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Multidisciplinary approach; Field (mathematics); Process (computing); Computer science; Data science; Management science; Sociology; Engineering; Linguistics; Biology; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001562541,0.001641133,0.001566661,0.002559688,0.001366144,0.003944285,0.002692408,0.001901701,0.2592817],"category_scores_gemma":[0.01121569,0.0006708238,0.001666107,0.005007696,0.0004694871,0.002688851,0.002276852,0.002302209,0.3200747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001774238,"about_ca_system_score_gemma":0.003114964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01887322,"about_ca_topic_score_gemma":0.03113955,"domain_scores_codex":[0.9971072,0.0004079443,0.000411814,0.001003697,0.0007368797,0.0003324641],"domain_scores_gemma":[0.9949733,0.0009222199,0.0005288386,0.001422492,0.001797231,0.0003559165],"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":[0.000151798,0.00002511156,0.001724984,0.0004842541,0.0000245512,0.00002410662,0.00002679988,0.00009754087,0.0000978795,0.0009665267,0.9890625,0.007314014],"study_design_scores_gemma":[0.0001206509,0.0000223443,0.004502031,0.0003902068,0.00003097407,0.0001109038,0.00008614713,0.0001447839,0.0002178536,0.001589005,0.9927607,0.00002452603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003952895,0.0002056049,0.0002838819,0.0002597444,0.0001133829,0.00005416117,0.989842,0.0005298532,0.008316098],"genre_scores_gemma":[0.001108865,0.0001859329,0.0005296494,0.0003919744,0.00003372983,0.0001753087,0.9901097,0.0001660114,0.007298758],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2592817,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01632295782062699,"score_gpt":0.4202463863517931,"score_spread":0.4039234285311661,"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."}}