{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001306644,0.002113892,0.001394438,0.004376457,0.001212005,0.003647137,0.003135986,0.002411806,0.1139635],"category_scores_gemma":[0.009342001,0.0007045312,0.002170028,0.006519293,0.0005645361,0.002676868,0.00347105,0.00237773,0.1860066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001845492,"about_ca_system_score_gemma":0.003231326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01556218,"about_ca_topic_score_gemma":0.03244752,"domain_scores_codex":[0.9978169,0.0003853644,0.0003212344,0.0007188615,0.0004731062,0.0002844563],"domain_scores_gemma":[0.9969192,0.0008460189,0.0003167473,0.0009278095,0.0007088072,0.0002815829],"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":[0.00007400157,0.00001986279,0.001018494,0.001078621,0.00003301177,0.00002650489,0.00003943924,0.0002085145,0.00009870871,0.001196027,0.991325,0.00488168],"study_design_scores_gemma":[0.00009555142,0.00001155627,0.001809887,0.0003863693,0.00001839712,0.00006622555,0.00006720113,0.0002452348,0.0001700186,0.001651792,0.9954614,0.00001631264],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000128102,0.0001523115,0.0001316955,0.0001333282,0.0000451961,0.00002104014,0.9972903,0.0004969578,0.001601056],"genre_scores_gemma":[0.0003091612,0.0001137151,0.0003838094,0.0001218861,0.00001085129,0.00007884305,0.9978795,0.0001067029,0.0009956431],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1139635,"threshold_uncertainty_score":0.3812459,"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."}}