{"id":"W3207579801","doi":"10.1136/ijgc-2021-esgo.137","title":"397 Molecular profiling of NSMP high-risk endometrial cancers of the PORTEC-3 trial – prognostic refinement and druggable targets","year":2021,"lang":"en","type":"article","venue":"International Journal of Gynecological Cancer","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"KRAS; Endometrial cancer; Microsatellite instability; Internal medicine; Immunohistochemistry; Oncology; Medicine; Hazard ratio; Proportional hazards model; Cancer research; Cancer; Biology; Colorectal cancer; Gene; Genetics; Allele; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001071104,0.0003150615,0.0007023765,0.0003835078,0.0002162915,0.001028697,0.0002768792,0.0003685835,0.002359696],"category_scores_gemma":[0.001520683,0.0002063656,0.0007606605,0.0005770607,0.0002268568,0.000406785,0.0003204923,0.0006548152,0.0003984485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004396631,"about_ca_system_score_gemma":0.000493303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005097179,"about_ca_topic_score_gemma":0.001418016,"domain_scores_codex":[0.9995754,0.0001594901,0.00004421533,0.00006251354,0.00008842757,0.00006998046],"domain_scores_gemma":[0.9996381,0.0001284011,0.00007153457,0.00005197569,0.00004788427,0.00006208438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0467891,0.0005668329,0.6242889,0.0005878056,0.001706951,0.0006629482,0.0001265084,0.004456662,0.03252153,0.001121513,0.006283864,0.2808873],"study_design_scores_gemma":[0.003954712,0.008675088,0.9257317,0.0002727228,0.002716227,0.00222912,0.0002646105,0.009011216,0.01622443,0.003146995,0.02771429,0.00005874685],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863814,0.006136551,0.0006740904,0.000787753,0.00008433626,0.00008834151,0.001548821,0.0000333602,0.004265403],"genre_scores_gemma":[0.991995,0.001427766,0.000928586,0.0004622347,0.0001064464,0.0001178963,0.00372377,0.00001781492,0.001220464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002359696,"threshold_uncertainty_score":0.00789392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0100526419847958,"score_gpt":0.2710167967117309,"score_spread":0.2609641547269351,"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."}}