{"id":"W2947590768","doi":"10.1186/s12862-019-1438-8","title":"Purifying selection does not drive signatures of convergent local adaptation of lodgepole pine and interior spruce","year":2019,"lang":"en","type":"article","venue":"BMC Evolutionary Biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Calgary","funders":"Genome Alberta; Genome British Columbia; Genome Canada","keywords":"Biology; Local adaptation; Pinus contorta; Adaptation (eye); Nucleotide diversity; Convergent evolution; Natural selection; Genetic diversity; Black spruce; Ecology; Selection (genetic algorithm); Evolutionary biology; Ecological selection; Population; Gene; Phylogenetics; Taiga; Genetics; Allele","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.000232796,0.0001760315,0.0002567211,0.0005977112,0.0003287447,0.0004393447,0.0001985648,0.0001295808,0.0004489047],"category_scores_gemma":[0.0005579593,0.00009301209,0.0001663913,0.0005018029,0.0004707997,0.0001061923,0.0002855321,0.0001811339,0.000060837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002813417,"about_ca_system_score_gemma":0.000201538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006302459,"about_ca_topic_score_gemma":0.01960778,"domain_scores_codex":[0.9998013,0.00002555935,0.00001340848,0.00007836865,0.00004789903,0.00003343228],"domain_scores_gemma":[0.9993303,0.0001485194,0.0002755258,0.00004566953,0.00009082029,0.0001092895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002950326,0.00004032102,0.8275011,0.0000601591,0.0001930896,0.000295127,0.000856047,0.0003975747,0.1640043,0.00009085954,0.00004319672,0.006223164],"study_design_scores_gemma":[0.000003587697,0.00002926366,0.9979348,0.000004028613,0.00002598939,0.0001768325,0.0001542542,0.0002460301,0.001303548,0.00002548815,0.00009363791,0.000002539661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997655,0.00003920297,0.00006809495,0.0000012372,2.85998e-7,0.000001139673,0.00002559844,0.000001700706,0.00009733319],"genre_scores_gemma":[0.9997084,0.0000184433,0.00010879,0.000004287879,7.022491e-7,0.000001781685,0.0001156312,0.0000013883,0.00004066636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006302459,"threshold_uncertainty_score":0.01253152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009012260871288,"score_gpt":0.2306169079137385,"score_spread":0.2205267853050256,"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."}}