[The periodic health examination: a comparison of United States and Canadian recommendations].
Bibliographic record
Abstract
OBJECTIVE: To compare recommendations of the Canadian Task Force on Preventive Health Care with those of the United States Preventive Services Task Force for periodic health examinations (PHEs), following the usual sequence of a medical interview. QUALITY OF EVIDENCE: Each task force reviewed the literature exhaustively and created a system of classification that indicated the quality of the evidence. MAIN MESSAGE: Two tables sum up the conclusions of the task forces with respect to preventive measures to be included in PHEs: one for adults generally and one for women specifically. Three other tables show measures for which recommendations are different or conflicting, as well as measures that might be excluded. Several forms and other materials for PHEs based on these comparisons can be found at http://medecinefamiliale.com/umf/emc/emp_guide.htm. Many recommendations are similar; in spite of this, many physicians fail to include them in PHEs. Certain factors could explain the differences between the recommendations, including the challenge of arriving at a standard scientific process for reviewing data, the fact that formulating recommendations is a social as well as a scientific process, and the fact that the CTFPHC is seriously underfunded. CONCLUSION: A scientific review of the literature, even when performed by experts using strict criteria, is not easy to standardize. The differences that our comparison revealed, some of which are substantial, highlight the need to further examine how recommendations are formulated. More research in this field would be helpful.
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 | 0.043 | 0.250 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".