{"id":"W2971114084","doi":"10.1097/pgp.0000000000000631","title":"Practical Guidance for Measuring and Reporting Surgical Margins in Vulvar Cancer","year":2019,"lang":"en","type":"article","venue":"International Journal of Gynecological Pathology","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Cancer Institute; National Institutes of Health","keywords":"Margin (machine learning); Medicine; Surgical margin; Basal cell; Vulvar cancer; Medical physics; Pathology; Surgery; Radiology; Resection; Computer science; Vulva","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":[0.001086839,0.00009965071,0.000512039,0.0001592184,0.0000157096,0.00001296472,0.00009149212,0.0001326585,0.0004153423],"category_scores_gemma":[0.004678536,0.00006757027,0.0001366356,0.00009070722,0.00005573111,0.0000920458,0.00005981772,0.0002910304,0.000005170152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000236658,"about_ca_system_score_gemma":0.0001307049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001375649,"about_ca_topic_score_gemma":0.00001804748,"domain_scores_codex":[0.9982388,0.00007911919,0.0009962078,0.0001958824,0.0002990973,0.0001909087],"domain_scores_gemma":[0.9976068,0.0009808135,0.0008506794,0.00006222733,0.0003925245,0.0001070129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002847349,0.0004471196,0.9739443,0.00002893506,0.0001460577,0.007851647,0.00004300695,0.00003227924,0.003126822,0.00123528,0.0000926438,0.01020454],"study_design_scores_gemma":[0.009870598,0.001738484,0.9732051,0.000146923,0.00006262692,0.006609382,0.00005788538,0.0001016842,0.0007572696,0.001671336,0.005671951,0.0001067641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904388,0.0005555826,0.0002139154,0.006452051,0.0009916966,0.0002306942,0.000006241507,0.000006308218,0.001104677],"genre_scores_gemma":[0.9940794,0.0003045519,0.004519527,0.0005677509,0.0003648592,0.00002144839,0.000002543134,0.000007576042,0.0001323925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01009778,"threshold_uncertainty_score":0.5600982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1124501646644141,"score_gpt":0.4196800796403727,"score_spread":0.3072299149759587,"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."}}