{"id":"W4399295395","doi":"10.1111/jop.13562","title":"Oral cancer detection and progression prediction using noninvasive cytology‐based DNA ploidy approach","year":2024,"lang":"en","type":"article","venue":"Journal of Oral Pathology and Medicine","topic":"Oral Health Pathology and Treatment","field":"Dentistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Cancer Society Research Institute; Mitacs; Michael Smith Health Research BC","keywords":"Medicine; Cytology; Cancer; Internal medicine; Biopsy; Proportional hazards model; Cohort; Retrospective cohort study; Oncology; Multivariate analysis; Pathology; Stage (stratigraphy); Gastroenterology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007521064,0.0001638527,0.0004229324,0.0002567577,0.0001916872,0.00001014098,0.0000426275,0.0003049688,0.00003576228],"category_scores_gemma":[0.00006657263,0.000105892,0.00004531329,0.0001506209,0.0004114498,0.0001658286,0.00002344402,0.0005197687,0.000002216629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007814483,"about_ca_system_score_gemma":0.0001128261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002628125,"about_ca_topic_score_gemma":0.00003900947,"domain_scores_codex":[0.9986835,0.0002607952,0.0004372707,0.0002442214,0.0001547772,0.0002194379],"domain_scores_gemma":[0.9993564,0.0000860177,0.0002317069,0.00008025413,0.0001032343,0.0001423292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004773876,0.0009311491,0.3841189,0.002475323,0.0007205014,0.05414558,0.003769509,0.0002014489,0.1897131,0.0005835316,0.001414597,0.3571525],"study_design_scores_gemma":[0.02317822,0.01994835,0.6239626,0.004710025,0.005046921,0.2611166,0.002242402,0.02470789,0.02483747,0.003944108,0.00548297,0.0008224288],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798246,0.01290634,0.004045071,0.0008307481,0.002085853,0.0001962922,0.00001419359,0.0000337333,0.0000631744],"genre_scores_gemma":[0.9968764,0.0005131467,0.00189876,0.0002315223,0.0003875738,0.00001167565,0.000006763166,0.00001444279,0.00005975036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3563301,"threshold_uncertainty_score":0.4318152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06029984591412756,"score_gpt":0.3952114149214719,"score_spread":0.3349115690073444,"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."}}