{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002423127,0.00006417437,0.00004809965,0.00002238006,0.00003758632,0.00001168417,0.0002304816,0.00005270815,0.00009571946],"category_scores_gemma":[0.0001487718,0.00004159293,0.0000382939,0.00004326701,0.0000438956,0.000001897775,0.0001135427,0.000135047,0.000006061849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005717617,"about_ca_system_score_gemma":0.00001186926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008776418,"about_ca_topic_score_gemma":0.000009510515,"domain_scores_codex":[0.9995385,0.000003938362,0.0001429862,0.00008232619,0.0001390668,0.00009318697],"domain_scores_gemma":[0.9996996,0.000005930055,0.0001036204,0.00007057629,0.0000989865,0.00002127362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001878253,0.00009049832,0.226704,0.00004220545,0.00007527525,3.141204e-7,0.0003264486,0.0002420276,0.6961139,0.06612185,0.002781719,0.007313893],"study_design_scores_gemma":[0.000861161,0.0005726148,0.04863481,0.00005471526,0.00001293446,0.00002963042,0.0005450816,0.01570702,0.7884551,0.0002330982,0.1445991,0.0002947739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6084779,0.000007044356,0.0009107522,0.0003453484,0.0001133757,0.00006652145,0.000001913481,0.00001072133,0.3900664],"genre_scores_gemma":[0.991299,0.00001272642,0.001519332,0.000252538,0.00005887157,8.404139e-7,0.00001209534,0.000005909154,0.006838696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3832277,"threshold_uncertainty_score":0.1696111,"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."}}