Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lyme disease arises from infection with pathogenic Borrelia species. In Canada, current case definition for confirmed Lyme disease requires serological confirmation by both a positive first tier ELISA and confirmatory second tier immunoblot (western blot). For surveillance and research initiatives, this requirement is intentionally conservative to exclude false positive results. Consequently, this approach is prone to false negative results that lead to underestimation of the number of people with Lyme disease. The province of New Brunswick (NB), Canada, can be used to quantify under-detection of the disease as three independent data sets are available to generate an estimate of the true human disease prevalence and incidence. First, detailed human disease incidence is available for the US states and counties bordering Canada, which can be compared with Canadian disease incidence. Second, published national serology results and well-described sensitivity and specificity values for these tests are available and deductive reasoning can be used to query for discrepancies. Third, high-density tick and canine surveillance data are available for the province, which can be used to predict expected human Lyme prevalence. Comparison of cross-border disease incidence suggests a minimum of 10.2 to 28-fold under-detection of Lyme disease (3.6% to 9.8% cases detected). Analysis of serological testing predicts the surveillance criteria generate 10.4-fold under-diagnosis (9.6% cases detected) in New Brunswick for 2014 due to serology alone. Calculation of expected human Lyme disease cases based on tick and canine infections in New Brunswick indicates a minimum of 12.1 to 58.2-fold underestimation (1.7% to 8.3% cases detected). All of these considerations apply generally across the country and strongly suggest that public health information is significantly under-detecting and under-reporting human Lyme cases across Canada. Causes of the discrepancies between reported cases and predicted actual cases may include undetected genetic diversity of Borrelia in Canada leading to failed serological detection of infection, failure to consider and initiate serological testing of patients, and failure to report clinically diagnosed acute cases. As these surveillance criteria are used to inform clinical and public health decisions, this under-detection will impact diagnosis and treatment of Canadian Lyme disease patients.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it