{"id":"W2484748210","doi":"10.1111/1755-0998.12570","title":"Exome capture from the spruce and pine giga‐genomes","year":2016,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Calgary","funders":"National Institute of Food and Agriculture; Alberta Innovates Bio Solutions; Ministry of Forests, Lands and Natural Resource Operations","keywords":"Biology; Genome; Exome; Evolutionary biology; Computational biology; Exome sequencing; Genetics; Gene; Mutation","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":[0.0005745756,0.000587692,0.0004221037,0.0007644363,0.0008614956,0.0008733498,0.00047595,0.0005074982,0.001905587],"category_scores_gemma":[0.00111233,0.0002785008,0.0006934858,0.0008869438,0.0002702145,0.0004123561,0.0009182588,0.0008816179,0.001022137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005335108,"about_ca_system_score_gemma":0.0006925859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007716022,"about_ca_topic_score_gemma":0.02621129,"domain_scores_codex":[0.9995739,0.00003701115,0.00002466702,0.0001426663,0.0001399274,0.00008186277],"domain_scores_gemma":[0.9995309,0.0001576218,0.00007300542,0.00006878295,0.0001093561,0.00006025179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002956606,0.00004811374,0.009484518,0.0004304241,0.0001034395,0.0003676963,0.0004380524,0.002529108,0.956256,0.001264176,0.002225219,0.02655761],"study_design_scores_gemma":[0.00009278992,0.0005196034,0.2770898,0.0002243501,0.0002751596,0.00265678,0.0009477406,0.02467758,0.5346258,0.004352843,0.1543664,0.000171223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7498699,0.003036336,0.1744,0.0005422622,0.0001622115,0.0005017176,0.06045577,0.002101149,0.008930541],"genre_scores_gemma":[0.6464527,0.002301263,0.1745006,0.001072438,0.00005996725,0.0005066856,0.1624847,0.0008232929,0.01179836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007716022,"threshold_uncertainty_score":0.01534224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004942711947257988,"score_gpt":0.1925625163095113,"score_spread":0.1876198043622533,"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."}}