{"id":"W4237003401","doi":"10.1515/iupac.88.0486","title":"Antepartum","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Maternal and Perinatal Health Interventions","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; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009097717,0.001063801,0.001229993,0.003186196,0.0006893254,0.001962121,0.001400776,0.001080985,0.09619079],"category_scores_gemma":[0.011417,0.0004728447,0.001424961,0.006969278,0.0002133889,0.001332589,0.001394668,0.001926435,0.04804391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159426,"about_ca_system_score_gemma":0.002688903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03268638,"about_ca_topic_score_gemma":0.03803563,"domain_scores_codex":[0.9982358,0.0003198899,0.000514905,0.0004358721,0.0003038722,0.0001895144],"domain_scores_gemma":[0.9962127,0.0009382487,0.0009675178,0.0005695751,0.001059437,0.0002524968],"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":[0.0004069249,0.00003073657,0.007878856,0.003114059,0.0001102585,0.0001118796,0.00006317262,0.0001126216,0.00007618467,0.001597418,0.9623091,0.0241889],"study_design_scores_gemma":[0.0003496166,0.00003183336,0.02661259,0.004138044,0.0001203416,0.0003751243,0.000259763,0.0001808569,0.0002312674,0.002211494,0.9654437,0.00004537145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006915296,0.001125268,0.0001912897,0.0003614365,0.0001301864,0.00007926215,0.9882961,0.0001544993,0.008970425],"genre_scores_gemma":[0.004401673,0.002832901,0.0009619589,0.001073618,0.0001560734,0.0005674732,0.9810906,0.0001130089,0.008802787],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9038092,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03845640105695506,"score_gpt":0.5136582039841646,"score_spread":0.4752018029272095,"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."}}