{"id":"W3021598508","doi":"10.1073/pnas.1913767117","title":"Metabolic cost of rapid adaptation of single yeast cells","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; United States - Israel Binational Science Foundation; Agence Nationale de la Recherche; National Science Foundation","keywords":"Adaptation (eye); Metabolic adaptation; Saccharomyces cerevisiae; Cellular adaptation; Yeast; Biology; Coupling (piping); Cell biology; Biological system; Computational biology; Metabolism; Neuroscience; Biochemistry; Materials science; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002904833,0.0002491955,0.0003433251,0.0002383989,0.0001833433,0.0005214668,0.0003363024,0.0003210066,0.000754776],"category_scores_gemma":[0.001005876,0.0001973246,0.0002129702,0.0002536843,0.0002690602,0.0005404279,0.0006823013,0.0005324023,0.0001647211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005202016,"about_ca_system_score_gemma":0.000206698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007034983,"about_ca_topic_score_gemma":0.0006231905,"domain_scores_codex":[0.999692,0.00004091247,0.00001741351,0.00009022147,0.0001196141,0.00003991804],"domain_scores_gemma":[0.9995072,0.0001905524,0.0001101307,0.0000709713,0.00005858274,0.0000626009],"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":[0.0002120706,0.00002844154,0.006072565,0.00005733817,0.00003146592,0.0001158904,0.00002526307,0.007879,0.9759833,0.0009125168,0.00008361731,0.008598434],"study_design_scores_gemma":[0.00002476187,0.0004705756,0.08233982,0.00001085393,0.00005830959,0.000480527,0.0001040057,0.1060777,0.8067871,0.00174012,0.001847213,0.00005914897],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905849,0.0003879938,0.008152308,0.0001035659,0.00001769144,0.000006779515,0.0001200049,0.00005372266,0.0005730102],"genre_scores_gemma":[0.9980579,0.0001524913,0.001494215,0.00001636597,0.000004639042,0.000009743544,0.00009451908,0.00001137623,0.0001586731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000754776,"threshold_uncertainty_score":0.003774345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05597984108345859,"score_gpt":0.2673945260230621,"score_spread":0.2114146849396035,"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."}}