{"id":"W4253131430","doi":"10.1515/iupac.76.0102","title":"Absorption, Systemic","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; Hazard; Relation (database); Multidisciplinary approach; Toxicology; Computer science; Medicine; Chemistry; Pharmacology; Data mining; Political science; Biology; Linguistics; Philosophy; Law; Organic chemistry","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":[0.0008748407,0.00143905,0.001187537,0.002861365,0.0008577572,0.003806806,0.001464082,0.001185319,0.2050439],"category_scores_gemma":[0.01008676,0.0004924308,0.001574517,0.005435987,0.0003975978,0.003481679,0.001884413,0.001510005,0.1738657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298655,"about_ca_system_score_gemma":0.002340348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01264184,"about_ca_topic_score_gemma":0.01900825,"domain_scores_codex":[0.998287,0.0002256335,0.0003179127,0.0006263808,0.0003819146,0.0001612222],"domain_scores_gemma":[0.9965525,0.001114189,0.0005083296,0.000784463,0.0008430174,0.0001975772],"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":[0.0002182821,0.00002958488,0.002650867,0.002376198,0.00006246043,0.00005298769,0.00005757341,0.0002029551,0.0002643169,0.001869722,0.95575,0.03646505],"study_design_scores_gemma":[0.0000653903,0.0000159152,0.004178323,0.0005342271,0.00004446953,0.0001078815,0.00005936799,0.0001156077,0.0001565386,0.001961494,0.9927413,0.00001927999],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007410442,0.001811546,0.0007628079,0.0003699808,0.0001728745,0.00007029393,0.9731113,0.001356342,0.0216037],"genre_scores_gemma":[0.004154261,0.001990917,0.002077897,0.000949535,0.0001017684,0.0002437622,0.9735961,0.0006430426,0.01624283],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2050439,"threshold_uncertainty_score":0.6859401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204769780771923,"score_gpt":0.3688961323032663,"score_spread":0.356848434495547,"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."}}