{"id":"W2979810324","doi":"10.1016/j.tgie.2019.150639","title":"Can artificial intelligence accurately diagnose endoscopically curable gastrointestinal cancers?","year":2019,"lang":"en","type":"article","venue":"Techniques and Innovations in Gastrointestinal Endoscopy","topic":"Gastric Cancer Management and Outcomes","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Endoscopic submucosal dissection; Endoscopic mucosal resection; Medicine; Resection; Dissection (medical); Endoscopy; Surgery","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003606878,0.0003269954,0.0004538956,0.0005983948,0.00008788143,0.00008466809,0.0001979186,0.00004463581,0.000407362],"category_scores_gemma":[0.0004249062,0.0003133551,0.00006545105,0.001221548,0.0001880217,0.0002219457,0.0001427697,0.0005483703,0.00002496833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003397993,"about_ca_system_score_gemma":0.0002882456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000786206,"about_ca_topic_score_gemma":0.0001754421,"domain_scores_codex":[0.9978077,0.00003840978,0.0007370593,0.0005302448,0.0003075036,0.0005791241],"domain_scores_gemma":[0.9988064,0.0002287281,0.0002049741,0.0003835673,0.0002484959,0.0001278073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000911261,0.0003397687,0.8426594,0.0003539667,0.00002294037,0.000466164,0.0001132338,0.00005090815,0.02772222,0.08940154,0.001302163,0.03665643],"study_design_scores_gemma":[0.01126274,0.04123906,0.5913821,0.03813339,0.0005376856,0.0517481,0.007875454,0.01684964,0.110332,0.1098184,0.01566666,0.005154821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457522,0.0001016035,0.02107495,0.01094487,0.0001813662,0.002652981,0.00003959456,0.0006949198,0.01855748],"genre_scores_gemma":[0.7883611,0.00005976922,0.2101604,0.0005191165,0.0001413584,0.0001535207,0.00004439794,0.00003395478,0.0005263652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2512773,"threshold_uncertainty_score":0.9999319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065685101390858,"score_gpt":0.3274856065839267,"score_spread":0.2868287555700181,"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."}}