{"id":"W2912093348","doi":"","title":"Proceedings of the 9th IAPR International Conference on Pattern Recognition in Bioinformatics - Volume 8626","year":2014,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Volume (thermodynamics); Computer science; Data science","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":[],"consensus_categories":[],"category_scores_codex":[0.0002056916,0.00008538811,0.00007598949,0.00004246804,0.00002185081,0.00002401532,0.000253762,0.00008089069,0.00009556078],"category_scores_gemma":[0.0001706003,0.00006050512,0.00003890529,0.00005545564,0.0000471552,0.000007588881,0.0001063766,0.0001116691,0.00003113046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009643863,"about_ca_system_score_gemma":0.00001604724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000146849,"about_ca_topic_score_gemma":0.00002122096,"domain_scores_codex":[0.9993978,0.000009747344,0.0002583649,0.00008400182,0.0001478766,0.0001022229],"domain_scores_gemma":[0.9995838,0.000005812179,0.0001629539,0.0001111725,0.0001154737,0.00002079872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002314091,0.0004896719,0.4994744,0.0006271084,0.0001455136,2.710097e-7,0.002353481,0.0004791064,0.08391596,0.007595453,0.03212803,0.3725596],"study_design_scores_gemma":[0.003073117,0.001369364,0.09147734,0.000531411,0.00003105638,0.00004899429,0.001509861,0.6553968,0.1880819,0.001591359,0.05596716,0.0009215469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7306265,0.000001453237,0.005377019,0.0008121804,0.0003612389,0.0001957857,0.00001609802,0.00001360257,0.2625961],"genre_scores_gemma":[0.9950647,0.00001198452,0.003072688,0.0004851556,0.00005354481,0.000006397584,0.00005394993,0.000006647048,0.001244959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6549177,"threshold_uncertainty_score":0.2467327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01197928623121896,"score_gpt":0.2384712719333201,"score_spread":0.2264919857021011,"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."}}