{"id":"W4282939738","doi":"10.1158/1538-7445.am2022-3813","title":"Abstract 3813: Unification of over 50 published single-cell RNA datasets covering over a 1000 patient samples with deep-learning reveals novel axes of tumor microenvironment variation","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Centre for Phenogenomics","funders":"","keywords":"Computer science; Workflow; Ground truth; Artificial intelligence; Atlas (anatomy); Deep learning; Machine learning; Computational biology; Biology; Database","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":[0.002818131,0.0007021383,0.0006855355,0.001500161,0.0005225074,0.00119135,0.0008497297,0.0008875212,0.002114156],"category_scores_gemma":[0.004772719,0.0002781094,0.001326991,0.001438987,0.0007126576,0.0005289639,0.00160365,0.001379161,0.001386307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008019342,"about_ca_system_score_gemma":0.001220699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005166084,"about_ca_topic_score_gemma":0.01246306,"domain_scores_codex":[0.9982635,0.0003299987,0.0001385419,0.0007443529,0.0003859136,0.000137699],"domain_scores_gemma":[0.9971969,0.00133529,0.0002494493,0.0005800381,0.0004667591,0.0001716728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002301894,0.0005761647,0.2464177,0.003244707,0.003213122,0.002055268,0.001213596,0.09229887,0.2538641,0.005080065,0.1030707,0.2866637],"study_design_scores_gemma":[0.0004807107,0.001242092,0.332715,0.0005012095,0.001231266,0.003522319,0.001513725,0.2752707,0.2144263,0.01721906,0.1514558,0.0004218406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7402794,0.005414155,0.1052419,0.002083904,0.0006337448,0.0002623279,0.1268049,0.01218065,0.007099209],"genre_scores_gemma":[0.6810406,0.001118056,0.07870504,0.001312478,0.0001771897,0.0004362505,0.232896,0.001242428,0.003071913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005166084,"threshold_uncertainty_score":0.0149039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03312181511764542,"score_gpt":0.2777606808536144,"score_spread":0.244638865735969,"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."}}