Development of the best-practice guidelines for the prevention of postpartum depression
Bibliographic record
Abstract
Postpartum depression poses a major public health problem with approximately thirteen percent of women experiencing this mood disorder after the birth of their baby. The significance of addressing postpartum depression lies in the potential to mitigate its negative effects on the health of women and their families, and the impact on their transition to parenthood. Further, prevention, early identification and treatment of this disorder are essential to reduce the suffering of women and their families. Best Practice Guidelines based on research evidence provide clinicians with ready access to a summary of the current state of evidence in a particular field, thus enabling clinicians to use quality evidence to enhance their clinical practice. The objective of this project was to augment the Perinatal Depression and Anxiety Best Practice Guidelines developed by the Ministry of Health and the British Columbia Reproductive Mental Health Program with a section on the prevention of postpartum depression.
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 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 | 0.063 | 0.154 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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".