Doença inflamatória intestinal: Revisão
Bibliographic record
Abstract
Inflammatory Bowel Disease (IBD) denotes a chronic illness of the gastrointestinal tract, characterized by persistent or recurrent clinical signs such as diarrhea, vomiting, loss of appetite and progressive weight loss. The IBD affects mainly middle aged dogs and cats, with no preference for gender. Although not having a clear etiology, most studies present it as a multifactorial disease, involving an exaggerated inflammatory immunological response against microbiota bacterias or antigens in dietary composition, with which the animal organism is not well adapted. The abnormal bacteria growth also seems to be related to IBD development. Specific dog breeds such as German Shepherd, West Highland White Terrier, Labrador, Basenji, Shar Pei and Poodle have a genetic predisposition to IBD, but it is not well elucidated. The diagnosis is established through the identification of the chronic gastrointestinal signs and the analysis both for image findings and biopsy histopathology. Some of the differential diagnosis of IBD includes giardiasis, linfoma, dietary hypersensitivity, E. coli infection and exocrine pancreatic insufficiency, that must be discarded with complementary exams. The treatment for IBD normally involves dietary changes and prescribed medications such as antibiotics and immunosuppressive drugs. The use of antibiotics is justified by the fact that bacterial antigens might be implicated in IBD etiology, but also because secondary bacterial development often occurs. Some authors argue the exclusive use of dietary therapy, because in some patients only this change can lead to parcial ou complete remission of the symptoms. There aren't studies about IBD prevention, because of its genetic etiology, but for the animal that has been already diagnosed with the disease there are some protocols to be followed, such as the use of hypoallergenic animal food, prebiotics, probiotics and synbiotics.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".