{"id":"W4388692040","doi":"10.1101/2023.11.11.566719","title":"Joint representation and visualization of derailed cell states with Decipher","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Fonds de Recherche du Québec - Santé; Marie-Josée and Henry R. Kravis Center for Molecular Oncology; National Cancer Institute; National Institutes of Health; Memorial Sloan-Kettering Cancer Center; Howard Hughes Medical Institute","keywords":"DECIPHER; Computational biology; Cell; Computer science; Biology; Visualization; Myeloid leukemia; Genetics; Artificial intelligence; Cancer research","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":[0.0004222325,0.000449778,0.000377447,0.0004527429,0.0001932686,0.0007933865,0.0004877831,0.0006322965,0.001921279],"category_scores_gemma":[0.0008795593,0.000358042,0.0004880081,0.0003186715,0.0005398248,0.0006144925,0.001160711,0.000709663,0.0003802161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005184018,"about_ca_system_score_gemma":0.0005647837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002341862,"about_ca_topic_score_gemma":0.004808863,"domain_scores_codex":[0.9998988,0.00002190444,0.000004373075,0.0000379619,0.00002469246,0.00001219785],"domain_scores_gemma":[0.9998158,0.00008010945,0.00002259845,0.00005115918,0.00001451716,0.00001579068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003599409,0.00006777359,0.009732197,0.0002236438,0.0001520197,0.0004142766,0.0004607031,0.685912,0.1727218,0.0372133,0.007048192,0.08569411],"study_design_scores_gemma":[0.000008088518,0.00001304411,0.00129879,0.000007063555,0.000006991422,0.00007351407,0.00003050765,0.9577041,0.02065794,0.01790946,0.002275525,0.00001484903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1511388,0.0003475487,0.8339788,0.000643045,0.00004878259,0.00003134155,0.003358507,0.008546976,0.001906266],"genre_scores_gemma":[0.7664978,0.0005068766,0.2254846,0.0001693147,0.00002319449,0.0001040549,0.003426821,0.001141954,0.002645287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002341862,"threshold_uncertainty_score":0.006427288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999686425117061,"score_gpt":0.2317805279822401,"score_spread":0.2117836637310695,"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."}}