Defining the epidemiology of bloodstream infections: the ‘gold standard’ of population-based assessment
Bibliographic record
Abstract
Bloodstream infections (BSIs) are a major cause of morbidity and mortality. Although population-based studies have been proposed as an optimal means to define their epidemiology, the merit of these designs has not been well documented. This report investigated the potential value of using population-based designs in defining the epidemiology of BSIs. Population-based BSI surveillance was conducted in Calgary, Canada (population 1.24 million) and illustrative comparisons were made between the overall and selected subgroup cohorts within five main themes. The value of population denominator data, and age and gender standardization for calculation and comparison of incidence rates were demonstrated. In addition, a number of biases including those related to differential admission rates, selected hospital admission, and referral bias were highlighted in non-population-based cohorts. Due to their comprehensive nature and intrinsic minimization of bias, population-based designs should be considered the gold standard means of defining the epidemiology of an infectious disease.
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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 | 0.125 | 0.203 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".