{"id":"W2789846220","doi":"10.1002/prca.201700084","title":"An MRM‐Based Cytokeratin Marker Assay as a Tool for Cancer Studies: Application to Lung Cancer Pleural Effusions","year":2018,"lang":"en","type":"article","venue":"PROTEOMICS - CLINICAL APPLICATIONS","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Genome British Columbia; Jewish General Hospital; University of Victoria","funders":"Narodowe Centrum Nauki","keywords":"Cytokeratin; Lung cancer; Medicine; Pleural fluid; Pathology; Pleural effusion; Oncology; Tumor marker; Cancer research; Cancer; Internal medicine; Immunohistochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001665052,0.0003248169,0.0006929518,0.000137245,0.0007392152,0.00006124638,0.0004306514,0.000196776,0.0001633092],"category_scores_gemma":[0.001520793,0.0002747887,0.0002371887,0.0006576501,0.0005049566,0.0001180041,0.0001945068,0.0004324962,0.0001318724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006371765,"about_ca_system_score_gemma":0.001057833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003631163,"about_ca_topic_score_gemma":0.0008798395,"domain_scores_codex":[0.996651,0.0001574995,0.001009365,0.001081351,0.0004783304,0.0006224872],"domain_scores_gemma":[0.9952439,0.001076648,0.0002704469,0.001149678,0.001751889,0.0005074525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.009812942,0.005855887,0.3615033,0.002796865,0.004115285,0.000005438817,0.002796116,0.0005042052,0.1695045,0.009959539,0.1353503,0.2977957],"study_design_scores_gemma":[0.01433831,0.004828158,0.1252688,0.001006813,0.002342922,0.000009368131,0.0006214358,0.1497112,0.03302591,0.004791371,0.6618333,0.002222309],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3014934,0.001330324,0.5784329,0.07519187,0.000438739,0.0408246,0.00113965,0.0005298643,0.0006186456],"genre_scores_gemma":[0.614781,0.001048088,0.1185038,0.0139222,0.004805786,0.245103,0.0002188666,0.000155639,0.001461713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5264831,"threshold_uncertainty_score":0.9999704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08450941785232464,"score_gpt":0.5404492689821476,"score_spread":0.455939851129823,"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."}}