{"id":"W2766384290","doi":"10.1002/ece3.3470","title":"Detection of barriers to dispersal is masked by long lifespans and large population sizes","year":2017,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada; Central Michigan University; National Science Foundation; College of Science and Engineering, University of Minnesota; Ministry of Natural Resources; Dental Foundation of Oregon","keywords":"Biological dispersal; Biology; Population; Population size; Ecology; Fragmentation (computing); Effective population size; Genetic divergence; Population fragmentation; Small population size; Isolation by distance; Genetic structure; Range (aeronautics); Divergence (linguistics); Genetic drift; Evolutionary biology; Genetic variation; Gene flow; Demography; Genetic diversity; Habitat","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":[0.0008239921,0.0001922433,0.0003118942,0.0001923586,0.0002675247,0.0005341654,0.0003492491,0.0002645812,0.0009667492],"category_scores_gemma":[0.003677204,0.0001887822,0.0002161257,0.0001294994,0.0004637774,0.000614844,0.0005156964,0.0003475073,0.00007332676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004076429,"about_ca_system_score_gemma":0.0002555423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003219554,"about_ca_topic_score_gemma":0.005030437,"domain_scores_codex":[0.999709,0.00009516571,0.00001673893,0.000110279,0.0000409271,0.00002805741],"domain_scores_gemma":[0.9965469,0.001768705,0.0009686314,0.0003194727,0.0001995717,0.0001966713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005996724,0.0001803847,0.8089532,0.0001273381,0.0002756928,0.0003216012,0.0005244933,0.03844558,0.1323635,0.001883271,0.0003150866,0.01601014],"study_design_scores_gemma":[0.00003789378,0.0005099105,0.8085002,0.00003049239,0.00013774,0.0003507258,0.0005370242,0.1732029,0.01308994,0.003042926,0.0005159157,0.00004432488],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965488,0.00002921068,0.002957443,0.00002190221,0.000001326693,0.000002373164,0.00002567683,0.00001788623,0.0003953616],"genre_scores_gemma":[0.9994578,0.000003938583,0.0004840801,0.000005648678,3.817818e-7,0.000001257126,0.0000118816,0.000002054632,0.00003300044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003219554,"threshold_uncertainty_score":0.006401598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005346070051123402,"score_gpt":0.2255742589205656,"score_spread":0.2202281888694422,"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."}}