{"id":"W4251326092","doi":"10.1515/iupac.76.0229","title":"Exogenous Substance","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; Toxicology; Computer science; Medicine; Pharmacology; Chemistry; 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":[0.001053863,0.001527186,0.001394343,0.004012703,0.0008163801,0.002623614,0.001593019,0.001353675,0.1448256],"category_scores_gemma":[0.007562876,0.0006111256,0.001322039,0.007005567,0.0004225721,0.002178708,0.001934427,0.001577814,0.139369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326543,"about_ca_system_score_gemma":0.002449621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025711,"about_ca_topic_score_gemma":0.01988361,"domain_scores_codex":[0.9983702,0.0002294647,0.0003292233,0.0005797361,0.0003809348,0.0001103753],"domain_scores_gemma":[0.996649,0.001165438,0.0004773835,0.0007548206,0.0007710404,0.0001823392],"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":[0.0001634385,0.00003843106,0.001859687,0.003477294,0.00005274871,0.0000555374,0.00005570523,0.000283138,0.0005567468,0.001471105,0.9753481,0.01663815],"study_design_scores_gemma":[0.00005062579,0.00001315996,0.002351815,0.0004630415,0.00002373421,0.00005041231,0.00004421289,0.000091061,0.000292666,0.000932077,0.9956692,0.00001804505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001839882,0.0003599,0.0001962015,0.0000589919,0.00004705389,0.00002892921,0.9967963,0.0002824117,0.00204631],"genre_scores_gemma":[0.0005137325,0.0003572246,0.0006622959,0.0001306751,0.00001324514,0.0001553293,0.995946,0.0000962679,0.002125252],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1448256,"threshold_uncertainty_score":0.48449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01516424021442905,"score_gpt":0.3731775199427665,"score_spread":0.3580132797283375,"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."}}