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Record W7098638558

Research

2016· article· en· W7098638558 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Ecology and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDiseaseRisk factorIncidence (geometry)ObesitySubclinical infectionEpidemiologyMortality rate
DOInot available

Abstract

fetched live from OpenAlex

Although the incidence of cardiovascular disease andassociated death rates have been steadily decliningin North America in recent decades, the opposite trend has been occurring in Aboriginal populations in Canada and the United States.1–3 For example, in Ontario, hospital admissions because of ischemic heart disease dou-bled in Aboriginal communities between 1981 and 1997, whereas over the same period the rates in the general pop-ulation declined.1 A major contributing factor appears to be the development of an excessive burden of cardiovascular risk factors in North American Aboriginal populations, most notably dramatic increases in the prevalence of dia-betes mellitus.4–7 Increased rates of other traditional cardio-vascular risk factors (e.g., hypertension, obesity and albu-minuria) have also been reported.5–7 In addition, novel nontraditional cardiovascular risk factors related to chronic subclinical inflammation (C-reactive protein), adipocyte

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.701
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2990.152

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 head0.134
GPT teacher head0.287
Teacher spread0.153 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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