{"id":"W4221142374","doi":"10.1093/nar/gkac331","title":"BioSimulators: a central registry of simulation engines and services for recommending specific tools","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Python (programming language); Computer science; SBML; Reuse; Software engineering; Software; Interface (matter); Systems engineering; Programming language; World Wide Web; XML; Operating system; Engineering","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":[0.0007404013,0.0001029013,0.0001552301,0.0001351411,0.000306845,0.00004395161,0.0002753384,0.00007950149,0.00007683437],"category_scores_gemma":[0.00006708321,0.0001103779,0.0000910092,0.0003057732,0.00008243791,0.000007620297,0.0003539946,0.0001350078,7.138058e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004469106,"about_ca_system_score_gemma":0.0000403097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007912069,"about_ca_topic_score_gemma":0.000004051822,"domain_scores_codex":[0.9985875,0.0001654345,0.000216333,0.0003544152,0.0003124798,0.0003638569],"domain_scores_gemma":[0.9991785,0.0001214982,0.00007492131,0.0003967368,0.0001462897,0.00008203166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007182934,0.0001851402,0.03353507,0.0003420244,0.0002926627,0.00000342456,0.0004909381,0.1685419,0.758834,0.0003372062,0.004820147,0.0318992],"study_design_scores_gemma":[0.001786442,0.001063203,0.01277982,0.00004439153,0.00005123169,0.00001173684,0.00262902,0.1395136,0.08728337,0.0004656381,0.7538785,0.0004930864],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972168,0.001285242,0.0007715383,0.0001716417,0.00006564846,0.0002968746,0.00006195118,0.000008739458,0.0001215635],"genre_scores_gemma":[0.9983145,0.0001511404,0.0007981767,0.00002324329,0.000240388,0.00004020228,0.0001611979,0.00002694057,0.0002441887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7490584,"threshold_uncertainty_score":0.4501078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04485659951256313,"score_gpt":0.3306183979115027,"score_spread":0.2857617983989396,"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."}}