{"id":"W4239804694","doi":"10.1515/iupac.88.0476","title":"Anomaly, Developmental","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":[0.001152133,0.001242674,0.0009936851,0.004354145,0.001018641,0.003122033,0.00199835,0.001244909,0.1704102],"category_scores_gemma":[0.0173736,0.0004203716,0.001550765,0.007293409,0.0005111909,0.002909702,0.002435035,0.001695028,0.09833465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001292108,"about_ca_system_score_gemma":0.003283007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01749465,"about_ca_topic_score_gemma":0.02826419,"domain_scores_codex":[0.9982315,0.000249262,0.000421429,0.0005548083,0.0003609121,0.0001821559],"domain_scores_gemma":[0.995082,0.001735353,0.0006854275,0.001031046,0.001205546,0.0002606201],"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":[0.0001078462,0.00001348091,0.003547402,0.002312384,0.00004516236,0.00004185333,0.00004954031,0.0001355941,0.00008747892,0.001624622,0.9705817,0.02145291],"study_design_scores_gemma":[0.00006262107,0.00001222091,0.006525486,0.001027923,0.00004702489,0.0001640116,0.00009961105,0.0001053807,0.00009229613,0.002654268,0.9891869,0.00002215643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002581959,0.0006608207,0.0003105714,0.0002771525,0.0001537203,0.00004000997,0.9926752,0.0003208838,0.005303456],"genre_scores_gemma":[0.001805814,0.001111988,0.001352235,0.0004988075,0.00006112343,0.0002642367,0.990509,0.0002054885,0.004191299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1704102,"threshold_uncertainty_score":0.5700789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283964168863476,"score_gpt":0.4429736968173627,"score_spread":0.4301340551287279,"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."}}