{"id":"W2890147601","doi":"10.1101/411058","title":"Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; Canada's Michael Smith Genome Sciences Centre; Genome British Columbia; University of British Columbia","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Cancer Research UK; BC Cancer Foundation; Terry Fox Research Institute; Canada Research Chairs; Michael Smith Health Research BC","keywords":"Genome; Biology; Computational biology; Genetics; Single cell sequencing; Replication timing; Mutation; Gene; Exome sequencing","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":[0.0008135724,0.0005137226,0.0006753201,0.0006874543,0.0004182204,0.0008559985,0.001045184,0.0005041098,0.008004198],"category_scores_gemma":[0.001565131,0.0004240664,0.0004400327,0.0009996454,0.0003742888,0.0008286685,0.0009123273,0.0005965147,0.002757064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006498051,"about_ca_system_score_gemma":0.001149095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003227573,"about_ca_topic_score_gemma":0.004320296,"domain_scores_codex":[0.9996492,0.00003627449,0.00002709622,0.0001419737,0.0001056761,0.00003980894],"domain_scores_gemma":[0.9993765,0.0001718396,0.00004797173,0.0002329832,0.000106686,0.0000640001],"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":[0.001592498,0.0001958219,0.0166092,0.001108296,0.0002546413,0.0005323787,0.0003762759,0.05140886,0.7656534,0.01275785,0.07192335,0.07758728],"study_design_scores_gemma":[0.0004572096,0.0001860374,0.03740696,0.0001217889,0.0001389864,0.0006427739,0.0002622627,0.3006248,0.5095549,0.03128397,0.1191677,0.000152524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3182461,0.0008520222,0.4294024,0.0008703105,0.0002072455,0.0002527497,0.192409,0.04536634,0.01239384],"genre_scores_gemma":[0.4236618,0.0006036594,0.3019775,0.0002574125,0.00005892588,0.0005387903,0.2607989,0.005512787,0.006590279],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008004198,"threshold_uncertainty_score":0.02677667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0112846033377902,"score_gpt":0.209073533745593,"score_spread":0.1977889304078028,"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."}}