{"id":"W2175322088","doi":"10.1111/j.0014-3820.2006.tb01149.x","title":"LOCAL ADAPTATION, PATTERNS OF SELECTION, AND GENE FLOW IN THE CALIFORNIAN SERPENTINE SUNFLOWER (HELIANTHUS EXILIS)","year":2006,"lang":"en","type":"article","venue":"Evolution","topic":"Sunflower and Safflower Cultivation","field":"Agricultural and Biological Sciences","cited_by":196,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Reserve System, University of California; University of California, Davis; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; David and Lucile Packard Foundation","keywords":"Local adaptation; Biology; Gene flow; Riparian zone; Adaptation (eye); Habitat; Helianthus; Ecology; Population; Selection (genetic algorithm); Sunflower; Evolutionary biology; Botany; Genetic variation; Gene; Agronomy; Genetics","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":[0.0002080883,0.0001467307,0.0001406568,0.0005511314,0.0002401267,0.0002626314,0.000181688,0.0001466676,0.0002819529],"category_scores_gemma":[0.0002763431,0.000108787,0.0001221557,0.0002276121,0.0003226413,0.0001642631,0.000207992,0.0001845263,0.00003759996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004958372,"about_ca_system_score_gemma":0.0001179141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006668423,"about_ca_topic_score_gemma":0.02129545,"domain_scores_codex":[0.9999115,0.00001603409,0.000007193095,0.00004106438,0.00001122347,0.00001297027],"domain_scores_gemma":[0.9997633,0.00005065132,0.0001021118,0.00001889884,0.00002320287,0.00004178155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000579135,0.0001657496,0.8002554,0.00007101223,0.0001184817,0.0003223737,0.001351661,0.001494935,0.1770543,0.00009125406,0.0001062858,0.01838934],"study_design_scores_gemma":[0.000002434937,0.00004451337,0.9991087,0.000001549894,0.000006335473,0.00004098613,0.0000991948,0.0002370721,0.0004042072,0.000008354366,0.00004366531,0.000002939765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999869,0.00003464412,0.00001980106,0.000002097309,2.111171e-7,7.674891e-7,0.00001236695,0.000001430323,0.00005964229],"genre_scores_gemma":[0.9997689,0.0000271027,0.00006461397,0.000004781767,7.037089e-7,0.000002533655,0.00006085571,0.000001089992,0.00006941541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006668423,"threshold_uncertainty_score":0.01325923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009035942139250921,"score_gpt":0.1880102172653344,"score_spread":0.1789742751260835,"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."}}