Diagnosis, Evaluation, and Management of the Hypertensive Disorders of Pregnancy: Executive Summary
Bibliographic record
Abstract
OBJECTIVE: This executive summary presents in brief the current evidence assessed in the clinical practice guideline prepared by the Canadian Hypertensive Disorders of Pregnancy Working Group and published by Pregnancy Hypertension (http://www.pregnancyhypertension.org/article/S2210-7789(14)00004-X/fulltext) to provide a reasonable approach to the diagnosis, evaluation, and treatment of the hypertensive disorders of pregnancy. EVIDENCE: Published literature was retrieved through searches of Medline, CINAHL, and The Cochrane Library in March 2012 using appropriate controlled vocabulary (e.g., pregnancy, hypertension, pre-eclampsia, pregnancy toxemias) and key words (e.g., diagnosis, evaluation, classification, prediction, prevention, prognosis, treatment, postpartum follow-up). Results were restricted to systematic reviews, randomized control trials, controlled clinical trials, and observational studies published in French or English between January 2006 and February 2012. Searches were updated on a regular basis and incorporated in the guideline to September 2013. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology-related agencies, clinical practice guideline collections, clinical trial registries, and national and international medical specialty societies. VALUES: The quality of evidence in the guideline summarized here was rated using the criteria described in the Report of the Canadian Task Force on Preventative Health Care (Table 1).
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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 | 0.028 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".