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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".