{"id":"W4248940426","doi":"10.1515/iupac.88.0919","title":"Hypertelorism","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":[0.003398317,0.001179096,0.001496061,0.006267576,0.001060645,0.004593892,0.002350575,0.001880546,0.2665775],"category_scores_gemma":[0.03181429,0.0006823201,0.001706418,0.01073196,0.0007093543,0.003965847,0.003948209,0.002002955,0.2170358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695092,"about_ca_system_score_gemma":0.003519446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007779179,"about_ca_topic_score_gemma":0.01527126,"domain_scores_codex":[0.9954156,0.001147161,0.001203287,0.0009383248,0.0009542841,0.0003413867],"domain_scores_gemma":[0.9857832,0.006622468,0.001383573,0.002761776,0.002871951,0.000576937],"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":[0.00005854419,0.000009255653,0.0003451269,0.001500212,0.00001978452,0.00001796568,0.00004023042,0.00007113716,0.00006626408,0.0007835808,0.9906246,0.006463275],"study_design_scores_gemma":[0.0000803981,0.000007976593,0.0009143802,0.0007300792,0.00001510175,0.00003477112,0.00005023088,0.00007694326,0.00009240476,0.001250788,0.9967308,0.00001607564],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001053953,0.0002270673,0.0002262084,0.0003064762,0.0001402335,0.00007058975,0.9943879,0.0005373457,0.003998864],"genre_scores_gemma":[0.000622994,0.0003144614,0.0009917993,0.000566197,0.0000726917,0.000559524,0.993038,0.0003238622,0.003510488],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2665775,"threshold_uncertainty_score":0.8917907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319216140942601,"score_gpt":0.4516194779444567,"score_spread":0.4384273165350307,"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."}}