{"id":"W4235724459","doi":"10.1515/iupac.88.0758","title":"Epithelium","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; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001441042,0.001320586,0.001183789,0.003514012,0.001038652,0.003708554,0.002270015,0.001720655,0.168569],"category_scores_gemma":[0.01147347,0.000593038,0.001833594,0.005691093,0.0004039133,0.002978387,0.002629735,0.001659579,0.1941456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001614708,"about_ca_system_score_gemma":0.002989958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01506265,"about_ca_topic_score_gemma":0.02834679,"domain_scores_codex":[0.9975816,0.0004047965,0.0004899121,0.0007653903,0.0005026591,0.0002555511],"domain_scores_gemma":[0.9956982,0.001058823,0.0004321874,0.001136575,0.001446008,0.0002282978],"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":[0.000113353,0.00001800082,0.001889599,0.001575294,0.000041146,0.00003210015,0.00004593277,0.0001691198,0.0001647246,0.00161137,0.9810542,0.01328512],"study_design_scores_gemma":[0.00005847492,0.00001140594,0.002490437,0.0006164525,0.00002399966,0.00006044094,0.00007779132,0.000113263,0.0001713067,0.001345905,0.9950138,0.00001665304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002215125,0.0003230423,0.0002819087,0.0002121547,0.0001071465,0.00005184756,0.992751,0.0004642568,0.005587164],"genre_scores_gemma":[0.0006111386,0.0002976132,0.0006377578,0.0003313817,0.00002156355,0.0001544362,0.994534,0.0001220124,0.003290179],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.168569,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163963918985444,"score_gpt":0.4544292117390541,"score_spread":0.4427895725491997,"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."}}