{"id":"W3020708255","doi":"10.1101/2020.04.23.058545","title":"flowCut — An R package for precise and accurate automated removal of outlier events and flagging of files based on time versus fluorescence analysis","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Terry Fox Research Institute","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Flagging; Computer science; Upload; Outlier; R package; Spurious relationship; Data mining; Anomaly detection; Gating; Process (computing); Database; Artificial intelligence; Machine learning; Cartography; World Wide Web","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":[0.00774815,0.003959627,0.002355867,0.004368231,0.001275765,0.003789248,0.003698898,0.00157225,0.06411291],"category_scores_gemma":[0.02221496,0.002119688,0.002696932,0.002100543,0.001226891,0.002804253,0.002883163,0.004271509,0.03970351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009561013,"about_ca_system_score_gemma":0.003759914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002634334,"about_ca_topic_score_gemma":0.002972817,"domain_scores_codex":[0.9952837,0.001087617,0.0006306807,0.001251251,0.001390036,0.0003566981],"domain_scores_gemma":[0.9920216,0.004491161,0.0008474886,0.001292147,0.001098969,0.0002486485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000780151,0.0001084657,0.004287581,0.002931025,0.0006324707,0.0005290749,0.0003833232,0.00351815,0.01988284,0.008324159,0.8553939,0.1032288],"study_design_scores_gemma":[0.0008973155,0.0002796249,0.01277918,0.0009271177,0.0004139732,0.001864663,0.0001938443,0.09032486,0.07957045,0.04666693,0.765502,0.000580176],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.003345271,0.0006964132,0.3332604,0.0005698931,0.0003563679,0.0006204311,0.07391477,0.5837983,0.003438095],"genre_scores_gemma":[0.02816516,0.0008961602,0.5277945,0.00138384,0.0003007925,0.004466242,0.1313262,0.299308,0.006359132],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.06411291,"threshold_uncertainty_score":0.214479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820469369229869,"score_gpt":0.2429171521207374,"score_spread":0.2247124584284387,"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."}}