{"id":"W4320710287","doi":"10.1111/1755-0998.13768","title":"The <scp>WZA</scp> : A window‐based method for characterizing genotype–environment associations","year":2023,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Biology; Linkage disequilibrium; Adaptation (eye); Local adaptation; Single-nucleotide polymorphism; SNP; Genetics; Evolutionary biology; Genotype; Allele; Allele frequency; Computational biology; Population; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005061575,0.0001967049,0.0001859485,0.00005289947,0.0004972991,0.00004433165,0.0003745854,0.0002577387,0.000006822972],"category_scores_gemma":[0.0004028709,0.0001692203,0.0001781571,0.0001147786,0.0001268131,0.000001845915,0.0001484527,0.000120304,0.00005298306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002296421,"about_ca_system_score_gemma":0.00006567746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003940448,"about_ca_topic_score_gemma":0.00002571006,"domain_scores_codex":[0.998395,0.0002421037,0.0002555976,0.0004372376,0.0001425992,0.000527414],"domain_scores_gemma":[0.9989135,0.0003756654,0.0001576077,0.0004188645,0.00004571775,0.00008869329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004729422,0.0001431117,0.01528285,0.00003136376,0.000565288,0.000006168038,0.0006099367,0.01053892,0.9558589,0.003081545,0.008347622,0.005487011],"study_design_scores_gemma":[0.001035454,0.0006929424,0.3612874,0.000005255085,0.0001256727,0.000006307968,0.0003691999,0.0006571881,0.08714067,0.002642264,0.5458726,0.0001650182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9516907,0.0004769127,0.04517195,0.001103999,0.0002431572,0.0006318007,0.00008147697,0.00005129836,0.0005487209],"genre_scores_gemma":[0.9216943,0.00008234123,0.06584254,0.003514983,0.0005786949,0.001020099,0.0008243633,0.0001414371,0.006301289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8687182,"threshold_uncertainty_score":0.6900605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097902052309328,"score_gpt":0.2507490727591745,"score_spread":0.2397700522360812,"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."}}