{"id":"W4283009155","doi":"10.1101/2022.06.14.496107","title":"Pan-cancer classification of single cells in the tumour microenvironment","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Public Health Ontario; University of Toronto; Ontario Institute for Cancer Research","funders":"University of Toronto; Ontario Institute for Cancer Research; Banting Research Foundation","keywords":"Cancer; Stromal cell; Tumour heterogeneity; Cancer cell; Biology; Transcriptome; Computational biology; Tumor microenvironment; Immune system; Cancer research; Medicine; Immunology; Gene; Genetics; Gene expression","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004230205,0.0003009469,0.0002808874,0.00008416487,0.00007965008,0.0000437874,0.0006643756,0.0002783682,0.00004596432],"category_scores_gemma":[0.0000240597,0.0002852861,0.0001477202,0.0001643291,0.0001165927,0.000004004142,0.000255806,0.0004064793,0.000004112988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001246654,"about_ca_system_score_gemma":0.0001981014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009766161,"about_ca_topic_score_gemma":0.00001499831,"domain_scores_codex":[0.9981664,0.0002049369,0.000436162,0.0006392333,0.0002643923,0.0002888591],"domain_scores_gemma":[0.998673,0.0000179182,0.0003185783,0.0008766075,0.00006293462,0.00005093397],"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":[0.00004433917,0.000400745,0.007771985,0.0001290672,0.00004579502,0.000004501685,0.00001901818,0.0002370139,0.9910767,0.00002555999,0.0002411182,0.00000413295],"study_design_scores_gemma":[0.0003035302,0.0000946807,0.09783219,0.00005688223,0.00004807944,6.616895e-9,0.00001527881,0.00004902771,0.8876822,6.302321e-7,0.01362126,0.0002962126],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959959,0.001972165,0.0003989629,0.0001861822,0.0006189396,0.0005120534,0.0002837911,0.00001552932,0.00001646633],"genre_scores_gemma":[0.9976044,0.001087532,0.00054069,0.0002191427,0.0002291603,0.000245281,0.000002912903,0.0000623435,0.000008564617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1033945,"threshold_uncertainty_score":0.9999599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992710983338829,"score_gpt":0.2188879424211141,"score_spread":0.1989608325877258,"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."}}