{"id":"W2125642929","doi":"10.1093/bioinformatics/btn440","title":"Local coherence in genetic interaction patterns reveals prevalent functional versatility","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Canada Research Chairs; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Epistasis; Gene; Computational biology; In silico; Biology; Gene interaction; Cluster analysis; Saccharomyces cerevisiae; Genetics; Function (biology); Partition (number theory); Computer science; Artificial intelligence","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":[0.001030771,0.0004217885,0.00058386,0.003810304,0.0004929141,0.001198749,0.0005221758,0.000560525,0.001342982],"category_scores_gemma":[0.006656356,0.00029215,0.0004153306,0.002888046,0.001063558,0.001159682,0.001461752,0.0004900533,0.0002728538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004402205,"about_ca_system_score_gemma":0.000410316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001115421,"about_ca_topic_score_gemma":0.001375631,"domain_scores_codex":[0.9991457,0.0001455013,0.0000763928,0.0003656493,0.0001785658,0.00008823704],"domain_scores_gemma":[0.9953324,0.002794039,0.0008202733,0.0004604095,0.0003310214,0.0002618755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001411575,0.0004106855,0.3694922,0.00113595,0.0005829202,0.001579755,0.00143622,0.07012188,0.256434,0.01956482,0.002659685,0.2751703],"study_design_scores_gemma":[0.0001426253,0.0005218775,0.3819667,0.00009294166,0.0004043443,0.003220283,0.0008844985,0.4712755,0.05772262,0.07677353,0.006846027,0.0001490331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8605794,0.0005781853,0.1353489,0.0002309538,0.00000703211,0.00005017685,0.0008591372,0.0007062974,0.001639873],"genre_scores_gemma":[0.9773331,0.0001310618,0.02143359,0.00003544421,0.00001734644,0.0000306568,0.0007624113,0.00004733786,0.0002089724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003810304,"threshold_uncertainty_score":0.005451322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005842178164167,"score_gpt":0.2350388322449486,"score_spread":0.2149804104633069,"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."}}