{"id":"W4387029309","doi":"10.5376/cmb.2023.13.0003","title":"Computational Molecular Biology Interdisciplinary Technological Integration and New Advances","year":2023,"lang":"en","type":"article","venue":"Computational Molecular Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Systems biology; Computational biology; Computer science; Biology; Computational model; Data science; Management science; Nanotechnology; Artificial intelligence; Engineering; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003403375,0.0002656567,0.000260536,0.0002979429,0.0001497139,0.00003953484,0.0003561347,0.0004209871,0.00002357048],"category_scores_gemma":[0.0004092238,0.0002327317,0.0001155182,0.0003755621,0.0008339662,0.000009617439,0.0008638336,0.0002257586,0.00008087439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002270003,"about_ca_system_score_gemma":0.0001805456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004650694,"about_ca_topic_score_gemma":0.000004071584,"domain_scores_codex":[0.9981463,0.0001574153,0.0004424298,0.0005857268,0.000210483,0.0004576213],"domain_scores_gemma":[0.9991271,0.0001072455,0.0001165667,0.0002261015,0.0001998619,0.0002230489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002182451,0.0001524822,0.001864631,0.00007770394,0.0002539459,0.00005225173,0.0001405811,0.01386423,0.4960148,0.1577859,0.003697182,0.3258781],"study_design_scores_gemma":[0.001134513,0.001217026,0.002411535,0.00002923729,0.00002068477,0.00008924046,0.0001912738,0.02571712,0.01141041,0.950081,0.007207517,0.0004904316],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1793327,0.001233727,0.8154773,0.002788079,0.0001794307,0.0002777157,0.00005687511,0.00008720037,0.0005670098],"genre_scores_gemma":[0.9617092,0.0001657939,0.03395637,0.0006897337,0.0001126088,0.00003311488,0.00319635,0.0000231411,0.0001137068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7922952,"threshold_uncertainty_score":0.9490525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01887304333335217,"score_gpt":0.3501770350842353,"score_spread":0.3313039917508832,"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."}}