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Record W2104421216 · doi:10.1093/ije/dyu141

Cohort Profile: The Manitoba Follow-up Study (MFUS)

2014· article· en· W2104421216 on OpenAlexafffundabout
Robert B. Tate, T. Edward Cuddy, Francis A.L. Mathewson

Bibliographic record

VenueInternational Journal of Epidemiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsUniversity of ManitobaManitoba Health
FundersCanadian Institutes of Health ResearchManitoba Health Research Council
KeywordsMedicineCohortIschaemic heart diseaseCohort studyGerontologyDiseaseLife course approachDemographyPhysical therapyInternal medicinePsychology

Abstract

fetched live from OpenAlex

The Manitoba Follow-up Study (MFUS) is Canada's longest running study of cardiovascular disease and ageing. The MFUS cohort consists of 3983 men recruited from the Royal Canadian Air Force at the end of World War II. At entry to the study, 1 July 1948, their mean age was 31 years, with 90% between ages 20 and 39 years. All study members were free of clinical evidence of ischaemic heart disease. The protocol of MFUS was to obtain routine medical examinations from these men at regular intervals over time. The research goal of the study was to examine the role that any abnormalities detected on routine electrocardiograms from apparently healthy men might play in the prediction of subsequent diagnoses of cardiovascular disease. Over the course of 65 years, about 35% of the cohort has documented evidence of ischaemic heart disease. The research focus was expanded in 1996 to explore the roles of physical, mental and social functioning in support of healthy and successful ageing. On 1 July 2013, 429 original cohort members were alive with a mean age of 92 years. Collaborative research with others outside the in-house team is welcomed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.045
GPT teacher head0.370
Teacher spread0.325 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2014
Admission routes3
Has abstractyes

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