{"id":"W4387485642","doi":"10.1101/2023.10.08.561337","title":"The fitness cost of spurious phosphorylation","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO; Université du Québec à Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Science Foundation; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Spurious relationship; Phosphorylation; Computer science; Economics; Biology; Cell biology; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004229189,0.0004468279,0.0003855015,0.000342055,0.0003571432,0.0007438496,0.0003618514,0.0004240547,0.001409217],"category_scores_gemma":[0.001630418,0.000151561,0.0002663925,0.0002601512,0.0003665689,0.0004651423,0.0008298786,0.0006506919,0.0002244455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005124361,"about_ca_system_score_gemma":0.0002441778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006833512,"about_ca_topic_score_gemma":0.0006361922,"domain_scores_codex":[0.9994836,0.0001391492,0.00004749685,0.00009289939,0.0001527434,0.00008402587],"domain_scores_gemma":[0.9990533,0.0003297151,0.0002145767,0.0001467004,0.0001137762,0.0001419812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002939602,0.0001113657,0.01838613,0.0001172567,0.00007263505,0.0004214948,0.0000424589,0.02078775,0.9436392,0.003878214,0.0002643499,0.01198523],"study_design_scores_gemma":[0.00005405794,0.001487127,0.1768465,0.00003727748,0.0001344848,0.003150882,0.0003817138,0.2570021,0.546484,0.01015919,0.004158917,0.0001038202],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950858,0.0001900492,0.00356425,0.0000972523,0.00001089403,0.000006391354,0.0001595392,0.0000353296,0.0008504355],"genre_scores_gemma":[0.9979677,0.00008492675,0.001326922,0.00002508212,0.000002828571,0.000009956151,0.0001618681,0.00002129892,0.0003994846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001409217,"threshold_uncertainty_score":0.004714251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118258981399994,"score_gpt":0.2327618316094776,"score_spread":0.2209359334694782,"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."}}