{"id":"W4390047245","doi":"10.1371/journal.pcbi.1011700","title":"Ten quick tips for fuzzy logic modeling of biomedical systems","year":2023,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Ministero dell'Università e della Ricerca; European Commission; Dipartimenti di Eccellenza","keywords":"Fuzzy logic; Computer science; Data science; Risk analysis (engineering); Artificial intelligence; Management science; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01004106,0.003495709,0.001525111,0.004324842,0.00159632,0.005948765,0.004003827,0.004678075,0.02812728],"category_scores_gemma":[0.06328554,0.001861252,0.001911546,0.002757618,0.00365348,0.01173689,0.003780618,0.01114356,0.01443271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002132398,"about_ca_system_score_gemma":0.001673079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002218124,"about_ca_topic_score_gemma":0.003708792,"domain_scores_codex":[0.9939161,0.003276234,0.0007259757,0.0004148301,0.001479636,0.0001872428],"domain_scores_gemma":[0.9714037,0.02068655,0.000746933,0.001993294,0.004505015,0.0006646307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001935803,0.0001360123,0.0006088887,0.002199982,0.0001483977,0.001267039,0.001257427,0.01819056,0.001914269,0.4571625,0.2041504,0.3127709],"study_design_scores_gemma":[0.0000569404,0.00006738864,0.0001578694,0.001279607,0.00003196514,0.0003629369,0.0002750526,0.02246744,0.0009951269,0.7720771,0.2021333,0.00009538661],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008717405,0.0104719,0.9496176,0.02226035,0.002496854,0.0002487776,0.0008075967,0.002822483,0.01040268],"genre_scores_gemma":[0.01437321,0.007957908,0.9596156,0.003902152,0.001666067,0.0006397449,0.0005692518,0.001091264,0.01018488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02812728,"threshold_uncertainty_score":0.09409511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03423075056816541,"score_gpt":0.2811292068519812,"score_spread":0.2468984562838158,"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."}}