{"id":"W2060817903","doi":"10.1158/0008-5472.can-08-3879","title":"Associations between Selected Biomarkers and Prognosis in a Population-Based Pancreatic Cancer Tissue Microarray","year":2009,"lang":"en","type":"article","venue":"Cancer Research","topic":"Pancreatic and Hepatic Oncology Research","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"inVentiv Health Clinical","funders":"National Cancer Institute; National Institutes of Health","keywords":"Tissue microarray; Hazard ratio; Oncology; Medicine; Pancreatic cancer; Internal medicine; Proportional hazards model; Population; Cancer; MUC1; Adenocarcinoma; Pathology; Confidence interval","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":[],"consensus_categories":[],"category_scores_codex":[0.001195635,0.0001454296,0.0005717298,0.0006098603,0.0002235833,0.00004130328,0.0001206926,0.0002066732,0.0003701365],"category_scores_gemma":[0.000780192,0.0001303562,0.00003336584,0.001822915,0.0001481104,0.00006911993,0.00002507797,0.0005688156,0.0000131534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001119667,"about_ca_system_score_gemma":0.001449966,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01378595,"about_ca_topic_score_gemma":0.00186551,"domain_scores_codex":[0.9974771,0.0003859035,0.0003582952,0.0004122024,0.0006464771,0.0007200725],"domain_scores_gemma":[0.9982665,0.0006838862,0.00006342652,0.0001986814,0.0005089026,0.0002785769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001882909,0.000123682,0.9729503,0.00007481331,0.0001188676,0.0000219293,0.0002201081,0.000002061272,0.01333555,0.00001725493,0.001414297,0.01153279],"study_design_scores_gemma":[0.001782709,0.0004725298,0.9932163,0.0002995878,0.00009084735,0.000001927277,0.0000378764,0.0002173192,0.0032481,0.0001506624,0.0003604123,0.0001216729],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841343,0.001805955,0.00001568312,0.01189624,0.00002160207,0.001379776,0.0001049336,0.00004221645,0.0005992655],"genre_scores_gemma":[0.9970627,0.0005064145,0.0005218246,0.0001565889,0.0001805406,0.0004677108,0.0001447938,0.00002086377,0.0009386075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.020266,"threshold_uncertainty_score":0.9927813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07765255560254787,"score_gpt":0.4462511567353189,"score_spread":0.368598601132771,"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."}}