Practice Guidelines for the Management of Infectious Diarrhea
Bibliographic record
Abstract
The widening array of recognized enteric pathogens and the increasing demand for cost-containment sharpen the need for careful clinical and public health guidelines based on the best evidence currently available. Adequate fluid and electrolyte replacement and maintenance are key to managing diarrheal illnesses. Thorough clinical and epidemiological evaluation must define the severity and type of illness (e.g., febrile, hemorrhagic, nosocomial, persistent, or inflammatory), exposures (e.g., travel, ingestion of raw or undercooked meat, seafood, or milk products, contacts who are ill, day care or institutional exposure, recent antibiotic use), and whether the patient is immunocompromised, in order to direct the performance of selective diagnostic cultures, toxin testing, parasite studies, and the administration of antimicrobial therapy (the latter as for traveler's diarrhea, shigellosis, and possibly Campylobacter jejuni enteritis). Increasing numbers of isolates resistant to antimicrobial agents and the risk of worsened illness (such as hemolytic uremic syndrome with Shiga toxin-producing Escherichia coli O157:H7) further complicate antimicrobial and antimotility drug
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.019 |
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".