{"id":"W4282916804","doi":"10.1158/1538-7445.am2022-463","title":"Abstract 463: Highly accurate machine learning assessment of immune-related pathologic response criteria (irPRC) scoring in patients with non-small cell lung carcinoma (NSCLC) treated with neoadjuvant anti-PD-1-based therapies","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Neoadjuvant therapy; Oncology; Digital pathology; Internal medicine; Radiology; Pathology; Cancer","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":[0.001654872,0.000297965,0.0004068906,0.0005866388,0.0002744473,0.0005314461,0.0003222813,0.0004337493,0.001160925],"category_scores_gemma":[0.002671204,0.0001697968,0.000314414,0.0003671353,0.0002628321,0.0003650963,0.0004163836,0.0004598086,0.000459973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004496679,"about_ca_system_score_gemma":0.0002902035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001891939,"about_ca_topic_score_gemma":0.003048336,"domain_scores_codex":[0.9992887,0.0001921427,0.00008213936,0.0002149968,0.0001553041,0.00006661497],"domain_scores_gemma":[0.9990625,0.0002380292,0.000211369,0.0001324058,0.0002592824,0.00009638467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002212916,0.000308825,0.8697999,0.0001252411,0.0001800674,0.0003371538,0.000212097,0.008472211,0.035384,0.0001421381,0.004042301,0.07878321],"study_design_scores_gemma":[0.00006090459,0.0006594617,0.8881128,0.00002370098,0.00009644886,0.0009948387,0.0001253325,0.09173132,0.01545916,0.0003338461,0.002359712,0.0000424606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932314,0.0002383617,0.004023979,0.0001217564,0.00003734398,0.00007332853,0.0009127132,0.0001379807,0.00122319],"genre_scores_gemma":[0.9954378,0.00004511925,0.002978305,0.00004022415,0.00001510458,0.00004843766,0.001117974,0.00001401736,0.0003029876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001891939,"threshold_uncertainty_score":0.008751929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02415591630071456,"score_gpt":0.3482531996067472,"score_spread":0.3240972833060327,"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."}}