{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002732642,0.0000874434,0.00009150372,0.0000217473,0.0001101196,0.0000201469,0.00008142809,0.00006439353,0.000120124],"category_scores_gemma":[0.0000231902,0.00003441822,0.00003558788,0.0003498814,0.00003179124,0.0001325878,0.00001309419,0.00007143269,0.000006448074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003470897,"about_ca_system_score_gemma":0.000006841225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00417887,"about_ca_topic_score_gemma":0.01571132,"domain_scores_codex":[0.9991684,0.00008841979,0.0002311987,0.0001756281,0.0001870736,0.0001492993],"domain_scores_gemma":[0.9997377,0.0000593477,0.00005960285,0.00003621266,0.00008768469,0.00001949106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000157911,0.0005347019,0.8218127,0.00002721018,0.00001581482,0.000005033088,0.001181832,0.009664421,0.1203048,0.001287077,0.001259357,0.04374915],"study_design_scores_gemma":[0.0001904283,0.00006817342,0.9707906,0.00001290639,0.000006921387,0.000008727765,0.0006083772,0.02485836,0.001478761,0.0004638266,0.001424414,0.00008855131],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919279,0.0001373405,0.007021385,0.0005165786,0.00007365127,0.0001598663,0.00003682133,0.00002213034,0.0001043604],"genre_scores_gemma":[0.9994673,0.00001168584,0.000136132,0.00004596762,0.0001367584,0.000008706589,0.0001385327,7.956513e-7,0.00005409943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1489778,"threshold_uncertainty_score":0.8767286,"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."}}