{"id":"W4250084675","doi":"10.1515/iupac.88.1281","title":"Renal","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; Data mining; 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":[0.001645229,0.001194448,0.001289447,0.003208366,0.0008880956,0.003743012,0.002407169,0.001571846,0.2167689],"category_scores_gemma":[0.01404462,0.0005667331,0.001619289,0.005665085,0.0003841994,0.003164432,0.0025099,0.001612645,0.2392983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474415,"about_ca_system_score_gemma":0.003196473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01386722,"about_ca_topic_score_gemma":0.02356712,"domain_scores_codex":[0.9974559,0.000458683,0.0005017039,0.0008126905,0.000510236,0.0002608236],"domain_scores_gemma":[0.9942772,0.001313545,0.0006180979,0.001557705,0.001897772,0.0003357726],"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":[0.0001216845,0.00001552024,0.001346551,0.001355169,0.00003838352,0.00002492882,0.00002877909,0.0001202778,0.0001193156,0.001198572,0.9832978,0.012333],"study_design_scores_gemma":[0.0000880259,0.00001153078,0.002289431,0.0006743117,0.00002449733,0.0000587667,0.00005357055,0.0001231556,0.0001578614,0.001492899,0.9950074,0.00001836657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001592265,0.0002844749,0.000239923,0.0002379417,0.000103502,0.00005068328,0.9927055,0.0005638134,0.005655013],"genre_scores_gemma":[0.0006805908,0.0003137066,0.0006283981,0.0004185705,0.00003376976,0.0001567288,0.9940672,0.0001521183,0.003548828],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2167689,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01237375052012267,"score_gpt":0.4526927249667047,"score_spread":0.440318974446582,"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."}}