{"id":"W7002052303","doi":"","title":"Machine learning in medical imaging: 8th international workshop, MLMI 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, proceedings","year":2017,"lang":"en","type":"other","venue":"CERN Document Server (European Organization for Nuclear Research)","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Conjunction (astronomy); Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006054516,0.00216136,0.002305762,0.003000238,0.0009585561,0.00537515,0.002805413,0.002019107,0.04935028],"category_scores_gemma":[0.007041493,0.0008379458,0.001039885,0.002430271,0.0009930979,0.00351304,0.003838301,0.004348369,0.04289711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002378988,"about_ca_system_score_gemma":0.005711512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01190937,"about_ca_topic_score_gemma":0.02946562,"domain_scores_codex":[0.9981237,0.0004398949,0.0001083343,0.000279405,0.0008239279,0.0002247166],"domain_scores_gemma":[0.9947317,0.001096659,0.0001113944,0.0008336179,0.002239231,0.0009874674],"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":[0.0001501384,0.0001542103,0.0002167883,0.0002778929,0.00004441397,0.00004920123,0.0000558434,0.001067926,0.001453303,0.002689976,0.8031672,0.1906732],"study_design_scores_gemma":[0.0001051486,0.0001404904,0.001928872,0.0004155806,0.00007075741,0.0003771079,0.0001748873,0.0320524,0.007825238,0.02089944,0.9359455,0.00006466962],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01245441,0.1123821,0.5743121,0.05131172,0.04775687,0.00111375,0.0320611,0.06812072,0.1004872],"genre_scores_gemma":[0.03593733,0.05791969,0.3137385,0.004728662,0.01410414,0.000833002,0.0781839,0.01258014,0.4819745],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04935028,"threshold_uncertainty_score":0.1650931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973416838334249,"score_gpt":0.2857609539876638,"score_spread":0.2660267856043212,"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."}}