Prevalence and impact of vasomotor symptoms due to menopause among women in Brazil, Canada, Mexico, and Nordic Europe: a cross-sectional survey: Erratum
Bibliographic record
Abstract
Lora Todorova, MPH, MBA, Rogerio Bonassi, MD, Francisco Javier Guerrero Carreño, MD, Angelica L. Hirschberg, MD, PhD, Nese Yuksel, BScPharm, PharmD, MSCP, Carol Rea, MMRS, Ludmila Scrine, MD, and Janet S. Kim, PhD In the original study by Todorova et al,1 there was an error in the third paragraph of the Study Objectives section of the Methods. The word “month” should have read “week”. The corrected paragraph is presented below. The MENQoL questionnaire included 29 questions in 4 domains: vasomotor, physical, psychosocial, and sexual functioning.25,26 MENQoL prompts respondents to rate how bothered they were by the problem on a scale from 0 (not at all bothered) to 6 (extremely bothered). The responses were then converted to 1 (not experienced in the past week) or 2 (experienced but not bothered) through 8 (extremely bothered). For each of the four domains, the mean scores for the individual questions in that domain were calculated,25,26 and total scores were calculated as the mean of the four domain scores.26
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".