{"id":"W4249945192","doi":"10.1515/iupac.76.0380","title":"Serum","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 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":[],"consensus_categories":[],"category_scores_codex":[0.001391357,0.001880272,0.00152889,0.003993219,0.0009539857,0.003482172,0.002538496,0.002114017,0.1712431],"category_scores_gemma":[0.01139559,0.0006322336,0.001470138,0.007153154,0.000360983,0.002814401,0.002384389,0.001657802,0.2150203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740274,"about_ca_system_score_gemma":0.00272269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0167155,"about_ca_topic_score_gemma":0.02923743,"domain_scores_codex":[0.9974834,0.0004058481,0.0004585072,0.0009186648,0.0005082562,0.0002254071],"domain_scores_gemma":[0.9957134,0.001172065,0.0005141935,0.001034043,0.001311791,0.00025462],"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":[0.00008514558,0.00001715266,0.0009784125,0.0009011448,0.00002398496,0.00002266165,0.00002657145,0.0001265587,0.0001109169,0.0006768729,0.9905682,0.006462445],"study_design_scores_gemma":[0.0001099147,0.00001425468,0.002738869,0.0005547548,0.00002410367,0.00007143145,0.00007713842,0.0002026032,0.0001927426,0.001715887,0.9942742,0.00002398258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009480099,0.0001278323,0.0001184958,0.0001000146,0.00003139871,0.0000205052,0.9978207,0.000314087,0.001372156],"genre_scores_gemma":[0.0002862285,0.0001188159,0.0003788557,0.0001482504,0.00001152236,0.0001036261,0.997727,0.00006842949,0.001157334],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1712431,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587844760530684,"score_gpt":0.4239256034243147,"score_spread":0.4080471558190079,"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."}}