{"id":"W4240507719","doi":"10.1515/iupac.88.0772","title":"Eventration","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":[0.001814746,0.001628706,0.00140438,0.004357603,0.0009214099,0.00316416,0.002528229,0.001836102,0.1206421],"category_scores_gemma":[0.01260183,0.0006841015,0.001953753,0.00624572,0.0004998613,0.002825508,0.002691146,0.002098283,0.1437298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001622056,"about_ca_system_score_gemma":0.003098094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01316267,"about_ca_topic_score_gemma":0.02498498,"domain_scores_codex":[0.9975037,0.0004590985,0.0005787073,0.0007083921,0.0005021259,0.0002479203],"domain_scores_gemma":[0.9949985,0.001542141,0.0006142017,0.001334969,0.001198403,0.000311894],"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":[0.0001266299,0.00002178765,0.001140317,0.002140284,0.00003974303,0.00002799027,0.00004007155,0.0002331474,0.0001529783,0.001168367,0.9870692,0.007839403],"study_design_scores_gemma":[0.000108502,0.00001619465,0.001981229,0.0005547418,0.00002200313,0.00004480482,0.00005992802,0.0001739267,0.0002219845,0.001301531,0.9954928,0.00002236835],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009948566,0.0001424452,0.0001527108,0.00008548543,0.00004825323,0.00004001673,0.9972478,0.0004740193,0.001709732],"genre_scores_gemma":[0.0003572686,0.0001675234,0.000556959,0.0001441646,0.00001462818,0.000202743,0.9972042,0.0001331376,0.001219445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1206421,"threshold_uncertainty_score":0.4035879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147721168213506,"score_gpt":0.4607276889080575,"score_spread":0.4492504772259224,"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."}}