{"id":"W4385213159","doi":"10.3390/cancers15143705","title":"Comprehensive Immune Profiling Unveils a Subset of Leiomyosarcoma with “Hot” Tumor Immune Microenvironment","year":2023,"lang":"en","type":"article","venue":"Cancers","topic":"Sarcoma Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of Calgary","funders":"European Network for Rare Adult Solid Cancers; Direction Générale de l’offre de Soins; Institut National Du Cancer; LabEx DEvweCAN; Ligue Contre le Cancer; Centre Léon Bérard; Institut Français de Bioinformatique; Institut National de la Santé et de la Recherche Médicale; Fondation ARC pour la Recherche sur le Cancer; Institut Claudius Regaud; Agence Nationale de la Recherche","keywords":"Immune system; Tumor microenvironment; Biology; Immunotherapy; Immunology; Computational biology; Cancer research","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":[0.0002632878,0.0001796809,0.0002812462,0.0007927109,0.0001949228,0.0003112128,0.0001253605,0.0001731767,0.0005301721],"category_scores_gemma":[0.0004384435,0.000123067,0.000198567,0.000416098,0.0002559718,0.0001473931,0.0003293558,0.0001668425,0.0001598901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001353175,"about_ca_system_score_gemma":0.0001350121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004232563,"about_ca_topic_score_gemma":0.001200737,"domain_scores_codex":[0.9998519,0.00002368144,0.00001197987,0.00005595912,0.00002996539,0.00002643364],"domain_scores_gemma":[0.9997558,0.00004925874,0.0001009147,0.00003396421,0.0000266696,0.00003332416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008939159,0.00005228458,0.6584641,0.00009870481,0.0001114206,0.0003222897,0.0003321552,0.0006499467,0.3218173,0.0001404897,0.0002977731,0.01681954],"study_design_scores_gemma":[0.00001321685,0.0001682934,0.9803481,0.000008753233,0.00007726892,0.0008480721,0.0002608513,0.002189678,0.01521405,0.0001915202,0.0006719547,0.000008275453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982286,0.0001762582,0.00110504,0.0000119882,0.000001247721,0.000008967175,0.0002619196,0.00001864146,0.0001874327],"genre_scores_gemma":[0.9977843,0.00006220924,0.001230316,0.00002624046,0.000006713006,0.00001886356,0.0007205388,0.000009785472,0.0001411711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007927109,"threshold_uncertainty_score":0.001773655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02228293377363826,"score_gpt":0.2638220023163342,"score_spread":0.2415390685426959,"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."}}