{"id":"W4385686800","doi":"10.4049/jimmunol.210.supp.226.07","title":"What did the T cell see? A deep-learning model of CD8+ T cell activation reveals sharp antigen discrimination at the single cell level","year":2023,"lang":"en","type":"article","venue":"The Journal of Immunology","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Antigenicity; Antigen; Flow cytometry; Cytotoxic T cell; CD8; T cell; Cancer research; Cell; Biology; Immunology; Immune system; In vitro","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":[0.0003235441,0.0004090113,0.0004495858,0.0002077361,0.000189998,0.0007455535,0.0005619882,0.001103742,0.001719997],"category_scores_gemma":[0.0007186592,0.0002282846,0.000429187,0.0002110707,0.0005220392,0.0005934043,0.0003112291,0.00101793,0.0002866482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007906213,"about_ca_system_score_gemma":0.0005261297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006997881,"about_ca_topic_score_gemma":0.004405229,"domain_scores_codex":[0.9999155,0.00001619194,0.000002425885,0.0000288682,0.000008413432,0.00002864272],"domain_scores_gemma":[0.9998533,0.00006832999,0.00001842992,0.000009195476,0.00002682582,0.00002392431],"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":[0.0001601548,0.00006124678,0.005603727,0.00002878803,0.00002378691,0.0001162491,0.00005166613,0.9697145,0.007418169,0.00255923,0.0009213484,0.01334112],"study_design_scores_gemma":[0.000002631684,0.000009247137,0.0002566241,0.000001298513,0.000002222632,0.000006119001,0.000003529807,0.9983873,0.0003180156,0.0009522003,0.0000585468,0.00000217879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8091647,0.000498678,0.1823854,0.002268694,0.0001114308,0.00004161879,0.0005786664,0.0002892099,0.004661616],"genre_scores_gemma":[0.99187,0.00007611583,0.005486953,0.0001426694,0.00001452375,0.00002518207,0.00009585518,0.00001225365,0.002276324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006997881,"threshold_uncertainty_score":0.01391429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07770327271561742,"score_gpt":0.3163797734850131,"score_spread":0.2386765007693957,"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."}}