{"id":"W3013187059","doi":"10.3791/60740","title":"Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment","year":2020,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Université de Montréal; Canadian Institutes of Health Research; Canadian Liver Foundation; Public Health Agency; Public Health Agency of Canada; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Computer science; Tumor microenvironment; Immune system; Computational biology; Visualization; Tumour heterogeneity; Biology; Artificial intelligence; Cancer; Immunology","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":[0.0006575828,0.0003525004,0.0002137695,0.001567072,0.0004627809,0.0006958612,0.0003022634,0.000500086,0.002132071],"category_scores_gemma":[0.0003964129,0.0003428057,0.0001972702,0.0004918588,0.0003555845,0.0004537005,0.0004237389,0.0006204735,0.0005539561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003083207,"about_ca_system_score_gemma":0.0003221501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006665181,"about_ca_topic_score_gemma":0.001585545,"domain_scores_codex":[0.999773,0.00004368183,0.0000163479,0.00007593477,0.00005728655,0.00003379645],"domain_scores_gemma":[0.9997655,0.00009719803,0.00002874155,0.0000372765,0.00004361673,0.00002767324],"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":[0.00004311612,0.00001836731,0.001067205,0.00006940559,0.000009141801,0.00006837617,0.00007022949,0.0004242183,0.9850519,0.0009310929,0.0002313405,0.01201575],"study_design_scores_gemma":[0.00001408549,0.00009755415,0.01248389,0.00002756968,0.00003028506,0.0007086715,0.0001412876,0.01721104,0.9620931,0.0009530249,0.006218348,0.00002115535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5450858,0.002603955,0.4411415,0.0005603678,0.00008888174,0.000196599,0.0008426192,0.002385968,0.007094239],"genre_scores_gemma":[0.4832667,0.002045945,0.5095429,0.0001617999,0.00003158933,0.0004548653,0.0004952716,0.0003470993,0.003653858],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002132071,"threshold_uncertainty_score":0.007132471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.081234312088494,"score_gpt":0.4121631756668766,"score_spread":0.3309288635783826,"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."}}