{"id":"W2496955077","doi":"10.1101/gr.201160.115","title":"Characterizing polymorphic inversions in human genomes by single-cell sequencing","year":2016,"lang":"en","type":"article","venue":"Genome Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"National Institute of General Medical Sciences; European Research Council; National Institutes of Health; University of British Columbia; Canadian Institutes of Health Research; Terry Fox Foundation; Canadian Cancer Society","keywords":"Biology; Structural variation; Computational biology; Genome; Genetics; Human genome; Population; 1000 Genomes Project; Reference genome; Genomics; DNA sequencing; Single cell sequencing; Phenotype; Genotype; Exome sequencing; Gene; Single-nucleotide polymorphism","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006864687,0.0001565813,0.0001599793,0.0002158468,0.0002232501,0.00004746122,0.0003932026,0.0001832301,0.0001152144],"category_scores_gemma":[0.00004405344,0.0001299621,0.0000715279,0.0002372924,0.0001912006,0.00001007563,0.0001872598,0.0002185162,0.0000635424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000190966,"about_ca_system_score_gemma":0.0001452581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001354709,"about_ca_topic_score_gemma":0.00006676327,"domain_scores_codex":[0.9980677,0.0001947796,0.0002502477,0.000487941,0.0002861788,0.0007130916],"domain_scores_gemma":[0.9992601,0.00003756194,0.00004016794,0.00039792,0.00009595376,0.0001682792],"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":[0.00003567776,0.0000914975,0.004584018,0.00002249699,0.0000105967,0.00001081685,0.0001537457,9.483051e-7,0.9934313,0.00001257948,0.0003170538,0.00132927],"study_design_scores_gemma":[0.0008635749,0.0003479811,0.000948385,0.00003796373,0.000002972721,0.000005829011,0.0001725996,0.000004326474,0.9603992,0.00006494661,0.03690881,0.000243375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941747,0.001597178,0.000202191,0.0005615552,0.00006216746,0.0002141798,0.00004468274,0.00001469013,0.00312872],"genre_scores_gemma":[0.9953319,0.000556496,0.0001082875,0.0001434809,0.0002011346,0.00002254037,0.00009319929,0.00004087259,0.003502049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03659175,"threshold_uncertainty_score":0.5299699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07230078745041116,"score_gpt":0.2962530975054994,"score_spread":0.2239523100550882,"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."}}