{"id":"W4412104478","doi":"10.1177/10668969251350264","title":"Small Samples, Big Insights: PD-L1 Experience of a Tertiary Institution","year":2025,"lang":"en","type":"article","venue":"International Journal of Surgical Pathology","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Concordance; Medicine; Lung cancer; non-small cell lung cancer (NSCLC); Internal medicine; PD-L1; Resection; Oncology; Immunotherapy; Radiology; Pathology; Cancer; Surgery","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":[0.004444371,0.0003493082,0.0003810889,0.001034754,0.001167156,0.001759731,0.0008404379,0.0003403915,0.00529355],"category_scores_gemma":[0.008756122,0.0003801599,0.0002683413,0.001142387,0.001081546,0.001145036,0.002614528,0.0007332423,0.001069694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002165277,"about_ca_system_score_gemma":0.002097822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003763164,"about_ca_topic_score_gemma":0.008028576,"domain_scores_codex":[0.9968624,0.001220887,0.0003237543,0.0007145067,0.0005352722,0.0003432305],"domain_scores_gemma":[0.9897383,0.002390919,0.002292563,0.001086696,0.00113033,0.003361209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003935701,0.0002009322,0.9494264,0.0001136099,0.00005972876,0.00209046,0.002546475,0.0003561529,0.003343914,0.0001725341,0.001972563,0.03932385],"study_design_scores_gemma":[0.00006288134,0.001768187,0.9425172,0.0003022291,0.0001384014,0.01496908,0.01439928,0.001836031,0.006531726,0.001045772,0.01631936,0.0001098632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927264,0.001365997,0.001910679,0.000856516,0.0000509388,0.00006830023,0.0002517366,0.00007085215,0.002698606],"genre_scores_gemma":[0.9967349,0.0005251889,0.001578981,0.0003844982,0.00007218349,0.00002948231,0.0001448145,0.000036192,0.0004936294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00529355,"threshold_uncertainty_score":0.02350438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042536100022873,"score_gpt":0.3142188818920481,"score_spread":0.2737935208918193,"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."}}