GI Classification Systems: Spanning the Globe
Bibliographic record
Abstract
Gastroenterology is replete with classification systems and criteria. These systems have sometimes been named for the cities in which they were created to facilitate easy recall by clinicians. To our knowledge, a report of classifications based on place of origin has never been published. A Medline search was conducted to identify geographically named classification systems. Twenty-one such classifications/criteria were identified. We present the criteria/classifications listed below in the format of a world map, all with in-depth descriptions; each system is illustrated on the map corresponding to the place where it was first published. Esophagus – Seattle Protocol for Barrett's Esophagus – LA Classification for Esophagitis – North Italian Endoscopic Club for the Study and Treatment of Esophageal Varices Stomach – Sydney Classification for Gastritis – Glasgow Dyspepsia Severity Score Colon – Bethesda Criteria for Testing Colorectal Tumors for Microsatellite Insta-bility – Amsterdam Criteria for HNPCC – Paris Classification for neoplasia of the GI mucosa Liver – Milan Criteria for Liver Transplantation for Hepatocellular Carcinoma – Barcelona Criteria for Liver Transplantation for Hepatocellular Carcinoma – UCSF Criteria for Liver Transplantation for Hepatocellular Carcinoma – Pittsburgh Criteria for Liver Transplantation for Hepatocellular Carcinoma – King's College Criteria for acetaminophen-induced and non-acetamino-phen induced acute liver failure Biliary – Mayo Risk Score for Primary Biliary Cirrhosis – Oslo Risk Score for Primary Biliary Cirrhosis – Milwaukee Classification for Sphincter of Oddi Dysfunction Pancreas – Atlanta Criteria for Pancreatitis – Cambridge Classification for diagnosis of chronic pancreatitis based on ERCP IBD/IBS – Vienna Classification for Crohn's Disease – Montreal Classification for Ulcerative Colitis – Rome Criteria for Irritable Bowel Syndrome
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.035 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".