Determinación del índice aterogénico y evaluaciön del riesgo de sufrir infarto en mujeres integrantes del club de madres Carlos Manuel Cox – del distrito de Buenos Aires – febrero 2013”
Bibliographic record
Abstract
The present research was aimed at determining the atherogenic index and Assess the Risk of Stroke in Women Members of the Mothers Club Carlos Manuel Cox-District of Buenos Aires - Montreal, in February 2013. The investigation arose from the observation of an increase in the percentage of women with heart disease, weight gain by, neglect by controlling your blood pressure and the influence of age and dietary habits and other styles life. We processed a total of 75 samples of blood plasma of women volunteers, and over 18 years. The results were stored in an Excel spreadsheet program with its own statistical analysis. Of which 44% of it had desirable total cholesterol, 32% moderately high and 24% a high level. Moreover serum HDL cholesterol level with 5% protective in volunteers, 59% of them at a desirable level and 36% high risk level. The results of the evaluation of suffering myocardial infarction according to the Framingham Score were 81.3% of the volunteers showed a very low risk, 10.7% of women subject to a low risk study and the remaining 8% of including a moderate risk of heart attack 10 years, so we conclude that the population is at a low percentage in coronary heart
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".