{"id":"W4391807049","doi":"10.1007/s12686-024-01351-9","title":"An improved genetic marker panel for conservation monitoring of upper Kootenay River burbot","year":2024,"lang":"en","type":"article","venue":"Conservation Genetics Resources","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of British Columbia","funders":"Montana Fish, Wildlife and Parks","keywords":"Watershed; Pedigree chart; Population; Population structure; Biodiversity; Biology; Ecology; Environmental resource management; Environmental science; Computer science; Genetics; Gene","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":[0.0001771914,0.0001931043,0.0001618493,0.000109006,0.0001227721,0.00008641101,0.0002368798,0.0002392383,0.00003024412],"category_scores_gemma":[0.00006086687,0.0001985321,0.0001189246,0.0001600374,0.0001404741,0.00001118024,0.00006020856,0.00007136344,0.000003578818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000126422,"about_ca_system_score_gemma":0.00008586248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005703792,"about_ca_topic_score_gemma":0.00001212207,"domain_scores_codex":[0.998747,0.00007278861,0.0003544885,0.0004303481,0.0001819305,0.0002134471],"domain_scores_gemma":[0.9990298,0.00004516016,0.0001234999,0.0003851634,0.0003256148,0.00009076574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001613595,0.00003252271,0.3806187,0.0001914765,0.0001325034,9.422729e-7,0.0008440778,0.001627217,0.6052396,0.00005670375,0.001336329,0.009758585],"study_design_scores_gemma":[0.0006067569,0.0003459158,0.6941544,0.00005541238,0.000115708,0.000008431679,0.000290752,0.02312962,0.1046789,0.0004222762,0.1758475,0.0003442547],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984122,0.002454412,0.01206622,0.0003263041,0.0004427154,0.0003901925,0.0001079018,0.00003346612,0.00005678293],"genre_scores_gemma":[0.9773959,0.0002290761,0.02065201,0.0002581675,0.0003889948,0.00002832003,0.000242781,0.00003508811,0.0007696403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5005606,"threshold_uncertainty_score":0.8095904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651356605776991,"score_gpt":0.2640512969450089,"score_spread":0.237537730887239,"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."}}