{"id":"W2134631886","doi":"10.1534/genetics.107.072926","title":"Adaptive Walks Toward a Moving Optimum","year":2007,"lang":"en","type":"article","venue":"Genetics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Biology; Adaptation (eye); Evolutionary biology; Fitness landscape; Genetics; Fixation (population genetics); Natural selection; Environmental change; Folding (DSP implementation); Phenotype; Evolutionary dynamics; Adaptive evolution; Stability (learning theory); Selection (genetic algorithm); Ecology; Gene; Climate change; Demography; Computer science; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000238203,0.0001566321,0.0001052363,0.00004794331,0.00006931453,0.00001681425,0.0002005425,0.0001842849,0.00002912632],"category_scores_gemma":[0.00003448927,0.0001664192,0.00008412777,0.00009942338,0.00008239896,0.000001194731,0.0001516831,0.00009281885,0.00004141059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002146622,"about_ca_system_score_gemma":0.00006674024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005337621,"about_ca_topic_score_gemma":0.0001039787,"domain_scores_codex":[0.9989125,0.00002283258,0.0002188866,0.0003115668,0.0001564957,0.0003777782],"domain_scores_gemma":[0.9993413,0.000008805156,0.00006062408,0.0003378305,0.0001051206,0.0001462957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002989864,0.000236294,0.01143574,0.00003597549,0.0002097267,0.00003367501,0.0005494262,0.01481105,0.9024935,0.00150307,0.0124734,0.05591916],"study_design_scores_gemma":[0.00404398,0.003041981,0.1178291,0.00005148985,0.0001762202,0.0002838205,0.002896198,0.04323165,0.3920653,0.002233536,0.4313933,0.002753373],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6153936,0.001768388,0.3718256,0.0001352335,0.000338025,0.0001926881,0.00001773819,0.00003463636,0.01029402],"genre_scores_gemma":[0.9635949,0.0002252024,0.03389873,0.0004828282,0.000334768,0.000004214774,0.00005603184,0.00002954572,0.001373756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5104282,"threshold_uncertainty_score":0.6786379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01252428216160527,"score_gpt":0.2570702233294987,"score_spread":0.2445459411678934,"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."}}