{"id":"W2770477678","doi":"10.1523/eneuro.0212-17.2017","title":"Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data","year":2017,"lang":"en","type":"article","venue":"eNeuro","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":161,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Institute of General Medical Sciences; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Campbell Family Mental Health Research Institute; National Institutes of Health; University of British Columbia; Canadian Institutes of Health Research; Children Neurodevelopmental Disorders Network","keywords":"Cell type; Transcriptome; Computational biology; Biology; Cell; RNA; RNA-Seq; Gene expression; Gene; Genetics","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":[0.003802088,0.0007390703,0.001113519,0.003168282,0.0007874277,0.00157897,0.0009670062,0.0003300171,0.002718189],"category_scores_gemma":[0.004339735,0.0004784348,0.0009426483,0.002857573,0.00035665,0.0008212794,0.001974118,0.0008017623,0.001632801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004095431,"about_ca_system_score_gemma":0.0008539733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008482262,"about_ca_topic_score_gemma":0.002346762,"domain_scores_codex":[0.9981112,0.0002808722,0.0002459978,0.0008387418,0.0003997714,0.0001233614],"domain_scores_gemma":[0.9964217,0.0008469865,0.0005476949,0.001338528,0.0006113615,0.0002337573],"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":[0.0004635339,0.000171867,0.02354228,0.0006834111,0.0004811026,0.0003800615,0.0005983649,0.003419232,0.8918333,0.001184668,0.003789031,0.07345322],"study_design_scores_gemma":[0.00007149368,0.0004413207,0.198716,0.0001585062,0.000651667,0.001213707,0.0006040751,0.02567047,0.6954086,0.006689353,0.07019334,0.0001814513],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3541055,0.001911171,0.5475317,0.0001748459,0.0001954573,0.0005855601,0.07829835,0.01235246,0.004844814],"genre_scores_gemma":[0.2848583,0.001291244,0.5536265,0.0003030461,0.0001133172,0.002316968,0.1511233,0.004334837,0.002032421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003802088,"threshold_uncertainty_score":0.02010763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122728133403085,"score_gpt":0.3141366434570413,"score_spread":0.2929093621230105,"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."}}