Incidence and clinical features of inflammatory bowel diseases in Zhongshan City of Guangdong Province
Bibliographic record
Abstract
Objective To investigate the incidence and clinical features of inflammatory bowel diseases (IBD) in Zhongshan City of Guangdong Province.Methods From July 2011 to June 2012,a prospective,population-based IBD epidemiological survey was conducted in Zhongshan City of Guangdong Province.All newly diagnosed IBD cases with Zhongshan census register were enrolled.The number of cases,Chinese age-standardized incidence and clinical features were analyzed.Results There were 48 new cases of IBD,of which 31 cases were ulcerative colitis (UC) and 17 cases were Crohn's disease (CD).The standardized incidence of IBD was 3.14/100 000,of which the incidence of UC was 2.05/100 000 and CD was 1.09/100 000.According to the Montreal classification,among 31 UC patients,11(35.5％) were proctitis,13 (41.9％) were left-sided colitis and seven (22.6％)were pancolitis.Among the 17 CD patients,lesions of four cases were terminal ileum type (one complicated with upper gastrointestinal bleeding),one case was colonic type and 12 cases were ileocolonic type (three cases complicated with upper gastrointestinal bleeding).Eleven cases were non-stricturing and non-penetrating type,four cases were stricturing type and two cases were penetrating type.Conclusions The incidence of UC is 2.05/100 000 and CD is 1.09/100 000 in Zhongshan City of Guangdong Province.Left-sided colitis is most common in UC and ileocolonic type is the most common in CD. Key words: Inflammatory bowel disease; Colitis, ulcerative; Crohn disease; Incidence; Guangdong
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".