{"id":"W4396885933","doi":"10.1038/s41467-024-48447-2","title":"Proteome partitioning constraints in long-term laboratory evolution","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Government of Canada; U.S. Department of Health and Human Services","keywords":"Proteome; Adaptation (eye); Context (archaeology); Biology; Phenotype; Experimental evolution; Computational biology; Flux (metallurgy); Gene; Evolutionary biology; Genetics; Chemistry","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":[0.00111631,0.0002468285,0.000406494,0.000232464,0.0005187122,0.0009927409,0.0006400604,0.0006266094,0.001217197],"category_scores_gemma":[0.002890823,0.0002608852,0.0002891386,0.0002482848,0.0008781336,0.001474186,0.001249328,0.0009021891,0.0002080711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009356728,"about_ca_system_score_gemma":0.0003254082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201442,"about_ca_topic_score_gemma":0.00112343,"domain_scores_codex":[0.9996593,0.00009911752,0.00002217784,0.0001025018,0.00006665729,0.0000502535],"domain_scores_gemma":[0.9989513,0.0003915958,0.0002164104,0.0002364597,0.00008712408,0.0001170789],"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":[0.0002565994,0.0001093179,0.02467926,0.000202257,0.0001417076,0.0004472916,0.0003376386,0.0362393,0.8794267,0.03379696,0.0006613152,0.02370173],"study_design_scores_gemma":[0.00009915103,0.0009835057,0.2608178,0.00008181999,0.000180904,0.001232054,0.001485709,0.3254911,0.2416443,0.1460311,0.02160553,0.0003471192],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825529,0.000621109,0.01388845,0.000496301,0.00002763541,0.00001064085,0.0001447421,0.000103276,0.002154935],"genre_scores_gemma":[0.9973935,0.0001706693,0.001987737,0.00008906645,0.000006513138,0.0000238915,0.00009513509,0.00001962157,0.0002139303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001217197,"threshold_uncertainty_score":0.00678879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00807211337483948,"score_gpt":0.299897066878876,"score_spread":0.2918249535040365,"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."}}