{"id":"W2911322539","doi":"","title":"Proceedings of the 24th international conference on Machine learning","year":2007,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Presentation (obstetrics); Library science; Computer science; Medical education; Medicine","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":[0.003745912,0.001568479,0.002150084,0.001919542,0.0008271663,0.005818401,0.002308377,0.002100028,0.1004016],"category_scores_gemma":[0.009330234,0.0003335925,0.00101474,0.001612475,0.001194272,0.004117442,0.002535453,0.004011112,0.06148677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190243,"about_ca_system_score_gemma":0.00257442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001424122,"about_ca_topic_score_gemma":0.001814024,"domain_scores_codex":[0.9949747,0.001382527,0.0004318458,0.0008285068,0.002026876,0.0003554706],"domain_scores_gemma":[0.9948698,0.001598771,0.0002334353,0.0009014033,0.001857588,0.0005390548],"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":[0.0001480195,0.00009242062,0.0008745357,0.0006194834,0.0001346814,0.0001168192,0.00009577049,0.001377939,0.001378864,0.009278403,0.629053,0.3568301],"study_design_scores_gemma":[0.00001807849,0.00009334041,0.001166347,0.0002844796,0.00003996014,0.0002914692,0.00009743101,0.005257912,0.0009425312,0.01048073,0.9812929,0.00003474036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01410912,0.1485252,0.2533079,0.03996506,0.1441942,0.001404414,0.01257411,0.01043501,0.3754849],"genre_scores_gemma":[0.1016669,0.08829773,0.1240527,0.01065338,0.03659561,0.001348443,0.04301048,0.002638697,0.5917361],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1004016,"threshold_uncertainty_score":0.3358768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006271625189994,"score_gpt":0.2612075380839381,"score_spread":0.2511448218320382,"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."}}