Abstracts from the 10th International Conference for Healthcare and Medical Students (ICHAMS)
Bibliographic record
Abstract
in patients who took ARBs, diuretics and/or CCB but the smallest number was shown in patients who took ACEi in combination with moxonidine (-20.07%).22.02% of smokers were non-dippers (-54.67%non-smokers).Odds ratio for getting hypertensive emergency in case patient had a non-dipper profile was 4.18 (Confidence Interval 1.02 -18.89, p < 0.05).Patients taking different medication (or none) did not have an increased chance for hypertensive emergency development (Odds Ratio 1.21, p = Not Significant).We didn't find any differences in the non-dipping profile incidence between genders (72.12% males, 72.83% females). ConclusionCombinations of all antihypertensive medication showed benefit over monotherapy.Higher 24-hour and nighttime blood pressure (non-dipping profile) was significantly associated with greater change for developing hypertensive emergency. O2. YouTube videos on hands-only (compression-only) cardiopulmonary resuscitation: a content analysis Reeya Gulve, Anuradha Joshi
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.295 | 0.089 |
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".