{"id":"W3207337285","doi":"10.1093/bib/bbab413","title":"sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution","year":2021,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Canadian Cancer Society Research Institute","keywords":"Copy-number variation; Biology; Transcriptome; Computational biology; Gene dosage; Gene; Genetics; Gene expression profiling; Genome; Gene expression","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":[0.0001417667,0.0001247086,0.0001735267,0.00003494068,0.00007602113,0.00003384413,0.00007545592,0.0001424975,0.00001459717],"category_scores_gemma":[0.0001483826,0.0001404921,0.00005007396,0.0001462629,0.00008897209,0.0000125037,0.0001203929,0.0000612927,0.000003629833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004856034,"about_ca_system_score_gemma":0.0001327864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007939031,"about_ca_topic_score_gemma":0.0001175202,"domain_scores_codex":[0.9990688,0.00001944759,0.0004274539,0.0001674915,0.0001174096,0.00019942],"domain_scores_gemma":[0.999411,0.00004115808,0.000153953,0.0002264944,0.0001164357,0.00005093409],"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":[0.0001487418,0.0003756268,0.01552267,0.0006884559,0.00007435197,0.000007942946,0.001918924,0.0007743704,0.9659951,0.00492,0.006914396,0.002659424],"study_design_scores_gemma":[0.001598905,0.0001323667,0.002492877,0.00007619598,0.0000416884,0.00003864885,0.0002505215,0.002874891,0.9756179,0.0004880515,0.01609492,0.0002930675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844918,0.0006797538,0.01139996,0.0004267557,0.0001697909,0.0001901754,0.0001463035,0.00001134842,0.002484113],"genre_scores_gemma":[0.9291092,0.0008132106,0.06879415,0.0006646322,0.0000540498,0.0000108477,0.0003733195,0.00001778487,0.0001628783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05739418,"threshold_uncertainty_score":0.5729103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114547254914039,"score_gpt":0.2209572802861319,"score_spread":0.2098118077369915,"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."}}