{"id":"W4416967010","doi":"10.22541/au.175382408.89466370/v4","title":"Flow matching for generative modeling in bioinformatics and computational biology","year":2025,"lang":"","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Vector Institute","funders":"National Energy Research Scientific Computing Center; U.S. Department of Energy; Lawrence Berkeley National Laboratory; National Institutes of Health; National Science Foundation","keywords":"Task (project management); State (computer science); Modelling biological systems; Computational model; Matching (statistics); Systems biology; Generative model","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005061576,0.001317693,0.001988621,0.002215566,0.000928995,0.003419189,0.002785502,0.002743785,0.005595436],"category_scores_gemma":[0.01254901,0.001048172,0.002673507,0.002672026,0.003135015,0.004219145,0.003738991,0.004279084,0.001412987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002508813,"about_ca_system_score_gemma":0.002471517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005290613,"about_ca_topic_score_gemma":0.003479859,"domain_scores_codex":[0.9979821,0.0009218432,0.0001397055,0.000420953,0.0004410582,0.00009429511],"domain_scores_gemma":[0.9944962,0.004341424,0.0002650009,0.0004231109,0.0003274948,0.0001469091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003221094,0.00003496631,0.000587131,0.0003503499,0.000110315,0.0001077355,0.0001577993,0.2779374,0.0007141667,0.6493673,0.005359924,0.06524068],"study_design_scores_gemma":[0.000009409924,0.00001284933,0.00009863911,0.00006838026,0.00001604073,0.00004804664,0.00001713159,0.589977,0.0002891745,0.3999256,0.009516357,0.0000213066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007539224,0.001998486,0.994544,0.0008679319,0.00008917908,0.00003006789,0.0001335484,0.0002271994,0.001355634],"genre_scores_gemma":[0.1377356,0.01538501,0.8350018,0.001448228,0.001443534,0.0008828258,0.001539314,0.0007218055,0.005841812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005595436,"threshold_uncertainty_score":0.02676851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1403620053251216,"score_gpt":0.4027636256984873,"score_spread":0.2624016203733657,"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."}}