{"id":"W4251537375","doi":"10.1515/iupac.88.1080","title":"Mucus","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":[0.00143102,0.001390034,0.001185285,0.003615655,0.000890217,0.003565966,0.002272757,0.001810233,0.2089275],"category_scores_gemma":[0.01153725,0.0005790871,0.001686914,0.00557568,0.0003473278,0.003038638,0.002487043,0.001563089,0.2282242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584291,"about_ca_system_score_gemma":0.002562967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01594043,"about_ca_topic_score_gemma":0.02899906,"domain_scores_codex":[0.997844,0.0003625024,0.0004561935,0.0006401686,0.0004835316,0.0002136651],"domain_scores_gemma":[0.9955422,0.001141521,0.0005003439,0.001068161,0.001491196,0.0002565891],"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":[0.00008432473,0.00001451493,0.001330109,0.001330292,0.00003054835,0.00002479346,0.0000328774,0.0001285863,0.0001180396,0.001098842,0.9868072,0.008999971],"study_design_scores_gemma":[0.00006679618,0.00001042283,0.002429051,0.0006254629,0.00001774926,0.00004590139,0.00006673836,0.0001074103,0.0001359199,0.001130249,0.9953478,0.00001657413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001222994,0.0001804428,0.0001513834,0.000146034,0.00006615186,0.00003682998,0.9954439,0.0004195566,0.003433351],"genre_scores_gemma":[0.0004356333,0.0002000274,0.0004860406,0.0002531259,0.00001928166,0.0001296922,0.9957151,0.0001188528,0.002642126],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2089275,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0119499794060872,"score_gpt":0.461689615806842,"score_spread":0.4497396364007548,"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."}}