{"id":"W2892646960","doi":"10.1007/s10682-018-9956-1","title":"The influence of habitat boundaries on evolutionary branching along environmental gradients","year":2018,"lang":"en","type":"article","venue":"Evolutionary Ecology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Veterinärmedizinische Universität Wien; Vienna Science and Technology Fund; Austrian Science Fund; European Science Foundation; Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Biological dispersal; Evolutionary dynamics; Animal ecology; Population; Range (aeronautics); Boundary (topology); Branching (polymer chemistry); Statistical physics; Small population size; Selection (genetic algorithm); Natural selection; Ecology; Stabilizing selection; Biology; Evolutionary biology; Habitat; Physics; Mathematics; Computer science; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000185084,0.0001606435,0.0001286339,0.00005212317,0.0008916322,0.00001375498,0.0002933012,0.0001606707,0.0000317363],"category_scores_gemma":[0.0001627363,0.0001397913,0.00008913711,0.00007864834,0.002033457,0.000008767425,0.0001889092,0.000116676,0.00009455025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000837258,"about_ca_system_score_gemma":0.0001758256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001688006,"about_ca_topic_score_gemma":0.0004153747,"domain_scores_codex":[0.998683,0.0001386093,0.0003115365,0.0003397029,0.0001829424,0.0003441708],"domain_scores_gemma":[0.9992753,0.00005653284,0.0001391838,0.0003867974,0.000071431,0.00007081121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008991082,0.0005700993,0.8398675,0.00001951206,0.0002609378,0.000006212458,0.0002587222,0.007056115,0.09328849,0.01274101,0.04380647,0.001225838],"study_design_scores_gemma":[0.0003936016,0.0009764672,0.9378484,0.000006491626,0.00001120421,0.00004728506,0.00006754748,0.0009204354,0.0005106594,0.001798508,0.057267,0.0001524437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969821,0.0007275813,0.0002184995,0.0004075768,0.0006577363,0.0001826272,0.00006199754,0.00001365856,0.0007482188],"genre_scores_gemma":[0.9975044,0.0001664263,0.0005453713,0.0003766308,0.0002411441,0.00002505651,0.0001403148,0.00001635725,0.000984338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09798087,"threshold_uncertainty_score":0.7492356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003023883018635999,"score_gpt":0.2126960303928955,"score_spread":0.2096721473742595,"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."}}