{"id":"W4238587258","doi":"10.1515/iupac.76.0181","title":"Conjugate","year":2016,"lang":"ca","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Hazard; Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001337758,0.001852459,0.001369287,0.003750671,0.001096021,0.003854206,0.002544643,0.001873648,0.2327364],"category_scores_gemma":[0.012114,0.0006383041,0.00160748,0.006185825,0.000397543,0.003426855,0.002662247,0.001774895,0.3013195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001721386,"about_ca_system_score_gemma":0.002608707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01505596,"about_ca_topic_score_gemma":0.02672618,"domain_scores_codex":[0.9974842,0.0003900971,0.0003905528,0.0009532453,0.0005382798,0.0002436809],"domain_scores_gemma":[0.995314,0.001180936,0.0004512812,0.001362773,0.00140271,0.0002883829],"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":[0.00005176316,0.00001334626,0.0006830723,0.0004983498,0.00001581372,0.00001270142,0.00001965876,0.00009294622,0.00006937682,0.0006519193,0.9920512,0.005839865],"study_design_scores_gemma":[0.00006985438,0.00001142391,0.001938869,0.0003351626,0.00001485344,0.00004054263,0.00007007838,0.00017263,0.000148274,0.001372132,0.9958078,0.00001836768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001175764,0.0001095842,0.0001508094,0.0001226012,0.00005172723,0.00002699519,0.9965563,0.0004304143,0.002434035],"genre_scores_gemma":[0.0003207933,0.00009532792,0.00041055,0.0001665216,0.00001551319,0.0001342773,0.9967823,0.0001141233,0.001960603],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7672636,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01626563607187764,"score_gpt":0.4197612774715853,"score_spread":0.4034956413997076,"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."}}