{"id":"W3013361160","doi":"10.1101/2020.03.27.012740","title":"CReSCENT: CanceR Single Cell ExpressioN Toolkit","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":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children’s Health Research Institute; Ontario Institute for Cancer Research; Western University; Hospital for Sick Children; Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Upload; Pipeline (software); Computer science; Scalability; Cloud computing; Pipeline transport; Expression (computer science); World Wide Web; Database; Operating system; Engineering; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001476243,0.0006136965,0.0004717186,0.00007867067,0.0001469415,0.0001803356,0.0007096299,0.0008329676,0.00006223786],"category_scores_gemma":[0.00007588817,0.0006626769,0.00026406,0.0001685349,0.0001019179,0.0000091212,0.0005947364,0.000614553,0.00003802046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053114,"about_ca_system_score_gemma":0.0004704993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007674527,"about_ca_topic_score_gemma":0.000005738054,"domain_scores_codex":[0.997275,0.0001083164,0.0004620609,0.00128715,0.0003148518,0.0005526295],"domain_scores_gemma":[0.9979858,0.00001144,0.0002986405,0.001072169,0.0002739613,0.0003579613],"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":[0.0001093991,0.0002413211,0.003365471,0.0004238864,0.00006499993,0.00002040757,0.000007091769,0.0001035383,0.9935086,0.000009385881,0.002142088,0.000003840759],"study_design_scores_gemma":[0.0005840511,0.0001211972,0.003125543,0.0002293914,0.00008393117,6.438897e-9,0.000001470541,0.00009569692,0.9474329,7.377118e-7,0.04756448,0.0007605349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868817,0.005379317,0.004002954,0.0003246251,0.002093819,0.0005994353,0.0004539911,0.0001891271,0.00007507732],"genre_scores_gemma":[0.9936116,0.0008926583,0.002915756,0.0006449565,0.001579365,0.0001295969,0.000004054216,0.0001898826,0.00003208864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04607562,"threshold_uncertainty_score":0.9995825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01928914874018055,"score_gpt":0.2167629739584632,"score_spread":0.1974738252182826,"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."}}