{"id":"W4236712168","doi":"10.1515/iupac.76.0429","title":"Uptake","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":[0.001751616,0.001965162,0.001589101,0.004674345,0.001290897,0.004375844,0.003458122,0.002279586,0.2046734],"category_scores_gemma":[0.01448297,0.0007486338,0.001908371,0.007546727,0.0004893902,0.004142251,0.003259456,0.002211278,0.2720725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002182337,"about_ca_system_score_gemma":0.003212063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02439327,"about_ca_topic_score_gemma":0.04597211,"domain_scores_codex":[0.9970741,0.0005042832,0.0004461217,0.001092414,0.0005761315,0.0003069728],"domain_scores_gemma":[0.994428,0.001594343,0.0004712371,0.001413884,0.001773981,0.0003184956],"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":[0.00005278721,0.0000130362,0.0008176799,0.0007445316,0.00002178553,0.00001781347,0.00003975611,0.0001313912,0.00006725689,0.0009041061,0.9921818,0.005008204],"study_design_scores_gemma":[0.00006363006,0.000009783527,0.001715879,0.0004844913,0.00001921232,0.00004035157,0.0001243025,0.0002047206,0.0001251163,0.001519937,0.9956698,0.00002283498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001205878,0.0001319539,0.0001424085,0.0001672683,0.00005481067,0.00002452912,0.9965669,0.000439752,0.002351761],"genre_scores_gemma":[0.0003194723,0.00009741458,0.0003896301,0.0001451228,0.00001299814,0.0001325495,0.9968402,0.0001412105,0.001921254],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2046734,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194098643947642,"score_gpt":0.4203507563899415,"score_spread":0.4009408919951773,"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."}}