{"id":"W4362541076","doi":"10.1158/1538-7445.am2023-5705","title":"Abstract 5705: Digital pathology based prognostic & predictive biomarkers in metastatic non-small cell lung cancer","year":2023,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Roche (Canada)","funders":"","keywords":"Atezolizumab; Medicine; Tumor microenvironment; Oncology; Immunotherapy; Lung cancer; Carboplatin; Internal medicine; Paclitaxel; Docetaxel; Immune system; Cancer; Cancer research; Nivolumab; Chemotherapy; Immunology; Cisplatin","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":[0.0007485953,0.0003466161,0.0002729596,0.001216795,0.0001555537,0.0006763728,0.0003318071,0.0002750666,0.003306399],"category_scores_gemma":[0.00134184,0.0001307218,0.0001582798,0.0008342373,0.0002138103,0.0003143331,0.0003934745,0.0002428827,0.0006241454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003695812,"about_ca_system_score_gemma":0.0003128549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001567745,"about_ca_topic_score_gemma":0.002664474,"domain_scores_codex":[0.9998,0.00003360747,0.00001847431,0.00005430283,0.00006953902,0.00002415787],"domain_scores_gemma":[0.9995683,0.0001252962,0.0001144505,0.00003464735,0.0001105187,0.00004693977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002282893,0.0002926995,0.6843832,0.0005575615,0.0002198224,0.0005330787,0.00007076218,0.01181974,0.08682547,0.0005215351,0.01103125,0.201462],"study_design_scores_gemma":[0.0001197553,0.0008146302,0.8155643,0.0000999128,0.0002889586,0.002052365,0.0001334632,0.09165687,0.07230254,0.001413661,0.01550972,0.00004366982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742395,0.002741542,0.00916695,0.0003564166,0.00006509358,0.0001220579,0.008620226,0.0005717404,0.004116545],"genre_scores_gemma":[0.9838269,0.0004197536,0.007787162,0.00004889651,0.00003378117,0.00005797823,0.006380459,0.00002279829,0.001422261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003306399,"threshold_uncertainty_score":0.01106095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0501117867464615,"score_gpt":0.4073571235675872,"score_spread":0.3572453368211257,"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."}}