{"id":"W4252249099","doi":"10.1515/iupac.81.0450","title":"Heterotherm","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Thermal Regulation in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Environmental risk assessment; Computer science; Ecology; Risk assessment; Biology; Data mining; 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":[0.000486541,0.000476699,0.0009620509,0.0003088938,0.00004826943,0.0000175872,0.0002613479,0.000495351,0.01326179],"category_scores_gemma":[0.0008238938,0.0003103905,0.00023598,0.0001728452,0.0002701881,0.00005103764,0.00009690155,0.0005742241,0.00001111164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005754131,"about_ca_system_score_gemma":0.0007759255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003556842,"about_ca_topic_score_gemma":0.00005790157,"domain_scores_codex":[0.9966463,0.00006854139,0.0006136138,0.0005152611,0.001708199,0.0004480802],"domain_scores_gemma":[0.9974369,0.0001000989,0.0002868278,0.001268863,0.0005437432,0.0003636061],"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":[0.0005135972,0.0002409321,0.00003115101,0.0003455216,0.0001823711,0.000202966,0.000009191362,2.811444e-7,0.0001179404,0.000004800417,0.9910356,0.007315634],"study_design_scores_gemma":[0.003169518,0.0005987423,0.0004828984,0.002018598,0.0003234724,0.0001757158,0.00001000588,0.00000237409,0.00005979943,0.00005583466,0.9927931,0.000309892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004403689,0.0007010002,0.0001473803,0.003391179,0.0009688819,0.0006052983,0.9933785,0.0002420713,0.0001253722],"genre_scores_gemma":[0.00006439514,0.0005060118,0.00006071133,0.001811905,0.003150105,0.00002253976,0.9916512,0.0001319058,0.002601175],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01325068,"threshold_uncertainty_score":0.9999348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635322757370827,"score_gpt":0.434093186942877,"score_spread":0.4177399593691687,"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."}}