{"id":"W3004894219","doi":"10.1016/j.isci.2020.100883","title":"Genotyping and Copy Number Analysis of Immunoglobin Heavy Chain Variable Genes Using Long Reads","year":2020,"lang":"en","type":"article","venue":"iScience","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institute of General Medical Sciences; University of Louisville; National Science Foundation; Indiana University; National Institutes of Health; Simon Fraser University","keywords":"IGHV@; Genotyping; Copy-number variation; Biology; Computational biology; Genetics; Immunoglobulin heavy chain; Genome; Locus (genetics); Gene; Genotype","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":[0.001081388,0.0004373363,0.0003993975,0.00113896,0.0003154525,0.0008830185,0.0006385816,0.0006492389,0.001319344],"category_scores_gemma":[0.002960393,0.0002450097,0.0004077132,0.0009448729,0.0003646737,0.0004023672,0.0005362388,0.0005389716,0.0007481695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004106712,"about_ca_system_score_gemma":0.0002793225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134402,"about_ca_topic_score_gemma":0.003478864,"domain_scores_codex":[0.9987519,0.0001974602,0.00007089225,0.0005097798,0.0003967506,0.00007330364],"domain_scores_gemma":[0.9984924,0.0005067491,0.0003565172,0.0003334575,0.0002511718,0.00005980235],"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":[0.0002124995,0.00006423637,0.02456497,0.0001945256,0.0001110651,0.0002134572,0.000432324,0.004924628,0.9110843,0.001949276,0.0003744545,0.05587419],"study_design_scores_gemma":[0.00001990301,0.0003026273,0.1273476,0.00006504447,0.0001515474,0.000844489,0.0002715169,0.06149619,0.7946308,0.004171156,0.01059772,0.0001014571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5889109,0.000784605,0.3980586,0.0001175618,0.00005688122,0.0001698871,0.006372437,0.001905701,0.003623509],"genre_scores_gemma":[0.6522189,0.0002884141,0.3378688,0.0001582109,0.00002186345,0.0001604783,0.005376163,0.00041174,0.003495437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001319344,"threshold_uncertainty_score":0.005719006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021725446479039,"score_gpt":0.2644518953894202,"score_spread":0.2442346409246298,"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."}}