{"id":"W4242761987","doi":"10.1515/iupac.78.0146","title":"Antagonism","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Relation (database); Computer science; Field (mathematics); Pesticide; Data science; Management science; Ecology; Engineering; Data mining; Biology; Mathematics; Linguistics","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":[0.001251772,0.001749789,0.001251402,0.004548678,0.001102903,0.003253927,0.002580487,0.001894612,0.1778948],"category_scores_gemma":[0.009806834,0.0005546102,0.00139784,0.007740173,0.0004063704,0.002782446,0.002256568,0.001787062,0.1963073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002149928,"about_ca_system_score_gemma":0.003328568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02418121,"about_ca_topic_score_gemma":0.0447437,"domain_scores_codex":[0.9977202,0.0003507207,0.0003769002,0.0008122131,0.0004850797,0.0002549437],"domain_scores_gemma":[0.9962363,0.0009340626,0.000480657,0.0008058657,0.001275267,0.0002679739],"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":[0.00005140326,0.00001308875,0.0008848816,0.0006097679,0.00001740041,0.00001726906,0.00002670191,0.00009826632,0.00008243018,0.0008381016,0.9935833,0.003777384],"study_design_scores_gemma":[0.00006653969,0.00001026067,0.002231546,0.0004470517,0.00001623746,0.00004914088,0.00008249043,0.0001230038,0.0001253272,0.001165205,0.9956636,0.00001966787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008421183,0.00007745228,0.00007086588,0.00009191301,0.00002350772,0.0000165408,0.9982796,0.0001238968,0.001232122],"genre_scores_gemma":[0.0002766042,0.00007735339,0.0002442316,0.0001103646,0.000008228897,0.00009982872,0.9979419,0.00004834888,0.001193046],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1778948,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673111295147219,"score_gpt":0.4197132699354546,"score_spread":0.4029821569839824,"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."}}