{"id":"W2238739307","doi":"10.1111/cobi.12674","title":"Role of genomics and transcriptomics in selection of reintroduction source populations","year":2016,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Genomics; Selection (genetic algorithm); Biology; Evolutionary biology; Computational biology; Population genomics; Genomic selection; Transcriptome; Genetics; Genome; Computer science; Gene; Genotype; Single-nucleotide polymorphism; Artificial intelligence; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001621851,0.0003587351,0.0003798572,0.0006317999,0.0002768259,0.0008278973,0.0003528008,0.0005105335,0.0003169864],"category_scores_gemma":[0.001046866,0.0001390385,0.0002355626,0.0003325834,0.0005840459,0.0006617356,0.0005519775,0.0004860181,0.0001501923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003738405,"about_ca_system_score_gemma":0.0002957216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000737093,"about_ca_topic_score_gemma":0.002181661,"domain_scores_codex":[0.9997011,0.00007878655,0.00001747507,0.0001106178,0.00005998512,0.00003202936],"domain_scores_gemma":[0.9992344,0.0003069776,0.0001978106,0.00005400153,0.000137371,0.0000693734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001686725,0.0000641669,0.05067911,0.0001749825,0.000058936,0.000237814,0.0004337911,0.001678022,0.9094977,0.001511736,0.0002276216,0.03526742],"study_design_scores_gemma":[0.00003775497,0.0005599439,0.7918896,0.0001582857,0.0002544437,0.0005991001,0.001398501,0.01875464,0.1678633,0.00940344,0.008945169,0.0001357204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9401391,0.003001438,0.05119074,0.001566988,0.00009767016,0.00009334794,0.0007935544,0.0002438316,0.002873454],"genre_scores_gemma":[0.9767637,0.001379361,0.0195774,0.0008364958,0.00003391364,0.00007913875,0.0006386195,0.00004764403,0.0006437298],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001621851,"threshold_uncertainty_score":0.008577287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01365116294209435,"score_gpt":0.2257548625225185,"score_spread":0.2121036995804241,"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."}}