{"id":"W4231582342","doi":"10.1515/iupac.88.0920","title":"Hypertrophy","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Computer science; 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":[0.001690912,0.001346194,0.001170755,0.003367986,0.0009107157,0.003129428,0.002270073,0.001626262,0.2165648],"category_scores_gemma":[0.01339841,0.0005430604,0.001746706,0.005217088,0.000386137,0.002794912,0.002267456,0.001576721,0.216485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001600803,"about_ca_system_score_gemma":0.002667868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01367013,"about_ca_topic_score_gemma":0.02455112,"domain_scores_codex":[0.9973609,0.0004345135,0.0005346399,0.0008935425,0.0005187963,0.000257609],"domain_scores_gemma":[0.9948248,0.001334512,0.0005218054,0.001270555,0.001776198,0.0002722737],"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":[0.0001288793,0.00001879292,0.00154928,0.001162766,0.00003458075,0.00002388832,0.00003346324,0.0001163646,0.0001133437,0.001094197,0.9858536,0.009870901],"study_design_scores_gemma":[0.0001159687,0.00001584828,0.003258437,0.0006578892,0.0000263382,0.00006081144,0.00009440134,0.0001355043,0.0001905405,0.001539537,0.9938816,0.00002314896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001603348,0.0001532317,0.0001887797,0.0001545964,0.00007870937,0.0000588428,0.9953234,0.0003827782,0.003499398],"genre_scores_gemma":[0.0005690377,0.0001711114,0.0006042164,0.0002907884,0.00002596501,0.0002515834,0.9949916,0.000119439,0.002976262],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2165648,"threshold_uncertainty_score":0.7244813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166978936569211,"score_gpt":0.4458002057667233,"score_spread":0.4341304164010312,"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."}}