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Record W2286375635

Update on age-appropriate preventive measures and screening for Canadian primary care providers.

2016· article· en· W2286375635 on OpenAlexaffabout
T Shimizu, Manon Bouchard, Cléo Mavriplis

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsCollege of Family Physicians of Canada
Fundersnot available
KeywordsGuidelineSpecialtyMedicinePreventive carePrimary careTask forceFamily medicinePreventive healthcareMEDLINETask (project management)Health careNursingPublic health
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize the best available age-appropriate, evidence-based guidelines for prevention and screening in Canadian adults. QUALITY OF EVIDENCE: The Canadian Task Force on Preventive Health Care recommendations are the primary source of information, supplemented by relevant US Preventive Services Task Force recommendations when a Canadian task force guideline was unavailable or outdated. Leading national disease-specific or specialty-specific organizations' guidelines were also reviewed to ensure the most up-to-date evidence was included. MAIN MESSAGE: Recommended screening maneuvers by age and sex are presented in a summary table highlighting the quality of evidence supporting these recommendations. An example of a template for use with electronic medical records or paper-based charts is presented. CONCLUSION: Whether primary care providers use a dedicated preventive health visit or opportunistic preventive counseling and screening in their patient encounters, this summary of evidence-based recommendations can help maximize efficiency and prevent important omissions and unnecessary screening.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.088
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0110.009
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.004

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.

Opus teacher head0.035
GPT teacher head0.258
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2016
Admission routes2
Has abstractyes

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