Introduction to the SAVE study (2011–15): Streptococcus pneumoniae serotyping and antimicrobial susceptibility: Assessment for Vaccine Efficacy in Canada after the introduction of PCV-13
Bibliographic record
Abstract
Streptococcus pneumoniae continues to be an important bacterial pathogen associated with invasive (e.g. bacteraemia) and non-invasive (e.g. community-acquired respiratory tract) infections worldwide. Surveillance studies conducted nationally and globally can assist in determining trends across geographical areas and allow comparisons between countries. SAVE is an ongoing, annual, national study focused on characterizing invasive isolates of S. pneumoniae obtained across Canada. This Supplement documents the initial 5 years of the SAVE study (2011-15) during which 6207 invasive isolates of S. pneumoniae were evaluated. The three manuscripts in this Supplement provide a comprehensive examination of the changing patterns of invasive S. pneumoniae obtained across Canada over a 5 year period. The data highlight the evolution of S. pneumoniae antimicrobial resistance and multidrug resistance, serotype distribution, genotypic relatedness and virulence under pressure by vaccination and antimicrobial usage. This allows both clinicians and researchers nationally and globally to view the current status of invasive pneumococcal infections in Canada.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".