{"id":"W4254472358","doi":"10.1515/iupac.76.0396","title":"Susceptible","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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; Biology; Data mining; 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":[],"consensus_categories":[],"category_scores_codex":[0.001431258,0.001778002,0.001222201,0.004339113,0.0009378113,0.003285554,0.002407536,0.001797445,0.1602199],"category_scores_gemma":[0.01098095,0.0006254516,0.001578886,0.006007356,0.000419323,0.002602587,0.002318784,0.001805574,0.1985312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001599898,"about_ca_system_score_gemma":0.002957887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01278001,"about_ca_topic_score_gemma":0.02592842,"domain_scores_codex":[0.9976981,0.0003831344,0.0003776748,0.0008469295,0.0004865641,0.0002075672],"domain_scores_gemma":[0.9961175,0.00117465,0.000417911,0.0009725983,0.001053704,0.0002636943],"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":[0.00007454083,0.00002078243,0.000972083,0.001041924,0.00002816151,0.00002267603,0.00003165943,0.0001654557,0.0001522306,0.0009059206,0.9901725,0.006412129],"study_design_scores_gemma":[0.00007676835,0.00001244858,0.001881827,0.00042047,0.00001869091,0.00004735984,0.00005616851,0.0001702281,0.0002031184,0.001162527,0.9959314,0.00001904234],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001051461,0.0001248037,0.0001299283,0.00008267219,0.00003639403,0.00002408869,0.99767,0.0003935274,0.001433529],"genre_scores_gemma":[0.0002410492,0.00009142236,0.0003682605,0.0001064664,0.000008461328,0.0001097292,0.9979553,0.00008679832,0.001032504],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1602199,"threshold_uncertainty_score":0.5359888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343513511917735,"score_gpt":0.3895761932570305,"score_spread":0.3761410581378531,"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."}}