{"id":"W4251342442","doi":"10.1515/iupac.88.1035","title":"Menstruation","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Menstrual Health and Disorders","field":"Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004760078,0.0003479113,0.0007405709,0.0002015113,0.0002358751,0.0000452795,0.0002127221,0.0004628287,0.002973685],"category_scores_gemma":[0.001136715,0.0002978288,0.0001512872,0.00007250742,0.0001473335,0.000060475,0.00007095587,0.0006317496,0.00001329652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003201823,"about_ca_system_score_gemma":0.002442581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003992499,"about_ca_topic_score_gemma":0.0009030823,"domain_scores_codex":[0.9974444,0.0000394521,0.0004633826,0.0004342873,0.00117671,0.0004417491],"domain_scores_gemma":[0.9974433,0.00003717711,0.0003823609,0.001212345,0.0004876333,0.0004372157],"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":[0.0004791297,0.0001938348,0.00004602164,0.0008300777,0.00005534182,0.00009377555,0.000009105712,2.058997e-7,0.000001268318,0.000003758364,0.9875853,0.01070215],"study_design_scores_gemma":[0.002312909,0.0005790048,0.0003413933,0.0005497523,0.0002648749,0.00006207264,0.00003437306,0.00001265562,0.000003700909,0.0000896829,0.9955037,0.0002458341],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005426124,0.0008147868,0.0000193521,0.001412315,0.001021394,0.0006118226,0.9949716,0.00005460501,0.0005514725],"genre_scores_gemma":[0.00007686117,0.001062935,0.0001305513,0.001163537,0.0009570788,0.00001604412,0.9957682,0.00003054625,0.0007942619],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01045631,"threshold_uncertainty_score":0.9999474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03237157096994728,"score_gpt":0.5078567499759775,"score_spread":0.4754851790060303,"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."}}