{"id":"W2043121779","doi":"10.1038/npre.2007.57.1","title":"Adaptive evolution and then what?","year":2007,"lang":"en","type":"preprint","venue":"Nature Precedings","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adaptation (eye); Population; Evolutionary dynamics; Ecology; Natural selection; Selection (genetic algorithm); Adaptive evolution; Variation (astronomy); Dynamics (music); Biology; Evolutionary biology; Computer science; Demography; Psychology; Artificial intelligence; Sociology; Gene","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":[0.001349247,0.0001520174,0.0002723888,0.0003169197,0.0002907887,0.001738055,0.0003312401,0.000731624,0.004536293],"category_scores_gemma":[0.003258249,0.00009633069,0.0001701791,0.0003308806,0.002401779,0.002417499,0.0004964988,0.001084645,0.0003449783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006567889,"about_ca_system_score_gemma":0.0002300391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007360416,"about_ca_topic_score_gemma":0.0004863117,"domain_scores_codex":[0.9995849,0.0001789304,0.00001156631,0.0001241111,0.00005291311,0.00004759953],"domain_scores_gemma":[0.9988583,0.0004887038,0.0001442383,0.0001781167,0.0002056282,0.0001250075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009726462,0.00006601343,0.02576044,0.0002088454,0.0001520037,0.0005161616,0.001406332,0.004252582,0.004503812,0.8637179,0.01495124,0.08436736],"study_design_scores_gemma":[0.000007938425,0.00001285583,0.01135459,0.00005122044,0.00002172331,0.0002737916,0.0006611217,0.006589118,0.0007699588,0.9638352,0.0164001,0.00002225206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5788462,0.0139055,0.07114168,0.2085742,0.002307373,0.00002895236,0.0004766424,0.0002980278,0.1244215],"genre_scores_gemma":[0.9853843,0.001879392,0.003039547,0.003401995,0.0003766834,0.00001164026,0.00007315361,0.00003381123,0.005799297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004536293,"threshold_uncertainty_score":0.01517546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006267812546328376,"score_gpt":0.2645199958251305,"score_spread":0.2582521832788022,"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."}}