{"id":"W2911590456","doi":"10.1111/evo.13691","title":"Local adaptation in dispersal in multi‐resource landscapes","year":2019,"lang":"en","type":"article","venue":"Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Biological dispersal; Resource (disambiguation); Biology; Ecology; Adaptation (eye); Local adaptation; Spatial ecology; Spatial analysis; Evolutionary biology; Geography; Computer science; Population","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":[0.0005447914,0.0001154124,0.0003426185,0.0003879857,0.0003926606,0.0006846592,0.000313017,0.0004576993,0.001091527],"category_scores_gemma":[0.002115217,0.0001803694,0.0002870368,0.0002584695,0.000863384,0.0008923847,0.0007742159,0.0004134869,0.0001268293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005022838,"about_ca_system_score_gemma":0.0001503095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009068629,"about_ca_topic_score_gemma":0.00144368,"domain_scores_codex":[0.9997827,0.00008054943,0.00001153841,0.00006239813,0.00002090353,0.00004194329],"domain_scores_gemma":[0.9991824,0.0003306775,0.0001988975,0.0001414118,0.000052517,0.00009407113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004608204,0.0002423722,0.3221714,0.0004371197,0.0007127724,0.003112529,0.001793521,0.2060496,0.3263865,0.0559065,0.001357915,0.08136895],"study_design_scores_gemma":[0.00008258555,0.0003237121,0.7043415,0.00006841264,0.0001242462,0.00298454,0.001058545,0.2115731,0.01105183,0.06423828,0.004020899,0.0001325301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906436,0.0002897801,0.007645006,0.0001347122,0.000004248671,0.000005275423,0.00001621748,0.00004450487,0.001216717],"genre_scores_gemma":[0.9988513,0.00006245842,0.0009194264,0.00001885102,0.00000219914,0.000003743447,0.00001328473,0.000005071969,0.0001237478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001091527,"threshold_uncertainty_score":0.003651559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005739993372076589,"score_gpt":0.2256592944442185,"score_spread":0.2199193010721419,"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."}}