{"id":"W4401728618","doi":"10.1186/s12859-024-05816-4","title":"Modeling relaxation experiments with a mechanistic model of gene expression","year":2024,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Laboratoire d'Excellence Ecofect; Agence Nationale de la Recherche; Université de Lyon; U.S. Department of Veterans Affairs","keywords":"DNA microarray; Computational biology; Relaxation (psychology); Population; Gene expression; Expression (computer science); Gene; Biology; Biological system; Computer science; Bioinformatics; Genetics; Neuroscience; Medicine","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":[0.001182843,0.0005318365,0.0006420947,0.000553996,0.0002886345,0.0007803155,0.001463838,0.001871896,0.001535143],"category_scores_gemma":[0.004185284,0.0005160893,0.001378814,0.0005010453,0.0008432089,0.0009944726,0.0006762954,0.001539114,0.0003014964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001085194,"about_ca_system_score_gemma":0.0007943155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004221365,"about_ca_topic_score_gemma":0.002703221,"domain_scores_codex":[0.9996389,0.0001085106,0.00001715515,0.0001330864,0.00005861025,0.00004371598],"domain_scores_gemma":[0.9979593,0.001521317,0.0002283852,0.0001322186,0.0001002203,0.00005863158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003621921,0.00003480029,0.001246191,0.0000518042,0.00002219765,0.00005746892,0.00005588392,0.9827543,0.005918844,0.00758741,0.0001130528,0.002121826],"study_design_scores_gemma":[0.000005316015,0.00001511349,0.000296103,0.000001918335,0.000006622402,0.00001582477,0.000005366151,0.9961852,0.0005549278,0.002685277,0.0002230605,0.000005185199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1925136,0.0002540451,0.803653,0.0005416616,0.00004748054,0.0001294323,0.0005923196,0.0003939665,0.001874447],"genre_scores_gemma":[0.8862898,0.0005289335,0.1073086,0.0002209342,0.00005798543,0.0006633949,0.0008597844,0.00007748653,0.003993066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004221365,"threshold_uncertainty_score":0.008393645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02118781300677493,"score_gpt":0.247326168600795,"score_spread":0.2261383555940201,"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."}}