{"id":"W2903593118","doi":"10.1109/tcbb.2018.2838658","title":"Multiscale and Multimodal Analysis for Computational Biology","year":2018,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computational biology; Multiscale modeling; Computer science; Biology; Cognitive science; Statistical physics; Bioinformatics; Psychology; Physics","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":[0.0003357804,0.000234908,0.0002819234,0.0003226274,0.0004459439,0.00004597984,0.0002105334,0.000348294,0.00002795621],"category_scores_gemma":[0.0001113476,0.0001992472,0.000141506,0.0002438883,0.001041741,0.00001572158,0.00003135228,0.000146217,0.00001854556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001495393,"about_ca_system_score_gemma":0.000099913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001435553,"about_ca_topic_score_gemma":0.00004836623,"domain_scores_codex":[0.9986027,0.000056971,0.0005177338,0.0003217229,0.0001419804,0.0003589047],"domain_scores_gemma":[0.9987687,0.0003211539,0.0001311505,0.0002190248,0.0003615484,0.0001983789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002860133,0.001514274,0.027487,0.0007433479,0.007777396,0.00000231717,0.002838401,0.08497935,0.01426461,0.00413631,0.002927934,0.8504689],"study_design_scores_gemma":[0.003579382,0.003896377,0.01393463,0.00002241566,0.0003146925,0.00004311365,0.0003641892,0.9502626,0.004637353,0.01224487,0.009987419,0.000712932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1392891,0.00007017348,0.8587225,0.0005205091,0.0002309881,0.0003381806,0.0007063045,0.0000223129,0.00009992012],"genre_scores_gemma":[0.8057988,0.0001373217,0.191998,0.0007141238,0.0001549655,0.00003359726,0.001063604,0.00001019779,0.00008938433],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8652833,"threshold_uncertainty_score":0.8125066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02073664505757557,"score_gpt":0.3209337557397452,"score_spread":0.3001971106821696,"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."}}