Care map for the management of asthma in a pediatric population in a primary health care setting
Bibliographic record
Abstract
Asthma is the most common chronic condition affecting children and the management of children experiencing this condition is of ongoing concern in Manitoba. In 1999 the Canadian Asthma Consensus Report (CACR), released by the Canadian Medical Association, provided management guidelines based on current evidence for efficacious treatment. The guidelines however, are too extensive and cumbersome to utilize on a daily basis in a busy primary heath care practice. The purpose of this practicum project was to simplify the CACR through the development of an evidence based care map, based on the major recommendations of the report. In order to ensure that the care map was of utility, both in content and format, the Care Map for the Management of Asthma in a Pediatric Population in a Primary Heath Care Setting was presented informally to the health care professionals at Family Medical Centre (FMC). Although FMC staff were supportive of the concept, areas of resistance to implementation of the care map were identified. Rationale for unexpected low rates of pediatric asthma clients managed in the clinic are discussed, and a revised evaluation framework for the care map is described.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".