{"id":"W4410943543","doi":"10.22541/au.174853973.36642913/v2","title":"A Beginner’s Guide to Structural Variants in Eco-Evolutionary Population Genomics: Everything You Wanted to Know","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet; Ministry of Business, Innovation and Employment; Fisheries and Oceans Canada; New Brunswick Innovation Foundation","keywords":"Population genomics; Genomics; Need to know; Population; Evolutionary biology; Biology; Genetics; Computer science; Sociology; Genome; Gene; Demography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003810473,0.001806088,0.001916748,0.00339411,0.001096728,0.004042201,0.00373015,0.005272481,0.09843703],"category_scores_gemma":[0.01912424,0.001074132,0.001621061,0.00308696,0.002302696,0.006588168,0.003065397,0.01099077,0.08018406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001384611,"about_ca_system_score_gemma":0.003152224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004456606,"about_ca_topic_score_gemma":0.007521041,"domain_scores_codex":[0.9984391,0.0004447465,0.0001657344,0.0002689335,0.0005919175,0.00008956729],"domain_scores_gemma":[0.9906475,0.005312649,0.0003550983,0.0007246787,0.001843518,0.001116438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002494936,0.00005755494,0.0002012752,0.000544575,0.00001666628,0.0001693086,0.0002175409,0.0002121697,0.000454511,0.007030942,0.8537734,0.137297],"study_design_scores_gemma":[0.00001098637,0.00001753531,0.0002468183,0.0006135196,0.000004821866,0.0002983663,0.00006657999,0.0001368069,0.0000776295,0.01382203,0.9846843,0.00002062058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.001014945,0.2388294,0.2355737,0.2482742,0.08153857,0.001448346,0.01768103,0.02025375,0.1553861],"genre_scores_gemma":[0.006341571,0.1817026,0.2598169,0.1940023,0.04286021,0.002443922,0.009358962,0.0104353,0.2930384],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09843703,"threshold_uncertainty_score":0.3293047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006152582578683939,"score_gpt":0.2787646253558109,"score_spread":0.2726120427771269,"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."}}