{"id":"W4256095188","doi":"10.1515/iupac.76.0398","title":"Systemic","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; Toxicology; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001427828,0.0009348973,0.001346265,0.0006128035,0.0001420755,0.0001151125,0.001244518,0.0008048964,0.009083036],"category_scores_gemma":[0.001266534,0.0006832011,0.0003476631,0.0004192239,0.000259851,0.000157989,0.0003787609,0.0008222823,0.0005307179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002466961,"about_ca_system_score_gemma":0.002084172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001632988,"about_ca_topic_score_gemma":0.0008543206,"domain_scores_codex":[0.9940071,0.0002842364,0.000946862,0.001016513,0.002797907,0.0009473958],"domain_scores_gemma":[0.9951103,0.0001630558,0.0007562288,0.00249749,0.001093829,0.0003790493],"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":[0.0002666278,0.0001756695,0.000004495996,0.0004496505,0.0002404096,0.0002561922,0.000005657039,8.833688e-7,0.00009011732,0.000008527408,0.9977388,0.0007629644],"study_design_scores_gemma":[0.001531858,0.0001592181,0.000004582846,0.002706248,0.0003117221,0.0002507564,0.00001801516,0.000001495398,0.00001619531,0.00006272601,0.9940551,0.0008820732],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004856239,0.002457698,0.00004745523,0.0001386746,0.001749624,0.000658029,0.9943842,0.0004298411,0.00008597283],"genre_scores_gemma":[0.00001906054,0.0006335297,0.00001925791,0.0001294746,0.002572143,0.00004201942,0.9953482,0.0002869384,0.0009493987],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008552318,"threshold_uncertainty_score":0.9995619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530919668744106,"score_gpt":0.4113473955741205,"score_spread":0.3960381988866794,"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."}}