{"id":"W3215343322","doi":"10.1093/nar/gkab1071","title":"Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization","year":2021,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Biology; Complementary DNA; cDNA library; Computational biology; RNA-Seq; RNA; Genetics; Genomic library; Molecular biology; Base sequence; DNA; Gene; Gene expression; Transcriptome","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003852293,0.0007919137,0.0009121404,0.0005713105,0.000418743,0.001015586,0.001061013,0.0008773445,0.001724454],"category_scores_gemma":[0.007110611,0.0005261109,0.0007231447,0.0007338074,0.0009315317,0.00135472,0.00106254,0.00142168,0.0006735798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071809,"about_ca_system_score_gemma":0.0008995141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001055293,"about_ca_topic_score_gemma":0.001797905,"domain_scores_codex":[0.9980248,0.0004884449,0.0001401098,0.0005256337,0.000616673,0.0002043798],"domain_scores_gemma":[0.9954305,0.003134375,0.0003288903,0.0005273138,0.0004598703,0.0001190543],"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":[0.0003143915,0.0001049144,0.002753,0.0002214064,0.00004340467,0.00006082146,0.00009767467,0.01825032,0.9645742,0.001420503,0.0001808773,0.01197856],"study_design_scores_gemma":[0.00001833333,0.0001360331,0.002136708,0.000008654857,0.00002551978,0.00004979923,0.00002973144,0.06513046,0.9303049,0.0009227199,0.001201018,0.00003607271],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.476984,0.0007083955,0.5163825,0.0002577839,0.0001369979,0.0002980271,0.0006075,0.002512512,0.002112181],"genre_scores_gemma":[0.7265971,0.0005832897,0.2692661,0.0002522223,0.00002317772,0.0004297616,0.0007586043,0.0004069436,0.001682792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003852293,"threshold_uncertainty_score":0.02037311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06219408132959854,"score_gpt":0.3130326406243722,"score_spread":0.2508385592947737,"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."}}