Fleet Management of the Travel Boat “Sopek Type” in Semarang
Bibliographic record
Abstract
The prevalence of maternal postnatal depression (PND) varies from 0% to 60% globally. This wide variety brings up the issue of whether PND is a universal medical condition or whether it is an idea impacted by cultural and social translations, and the labelling of signs and symptoms. The objective of this review was to understand women’s experience of PND in different countries. Studies reporting women’s experiences of PND were searched through databases of CINAHL, PubMed, MEDLINE, Psy INFO and ASSIA databases using specific key words. Articles published between 2006 and 2016 were filtered for inclusion criteria. A total of 27 studies on maternal experience of PND conducted in ten different countries including America, Canada, South Africa, United Kingdom, Norway, Australia, New Zealand, Bangladesh, China, and Taiwan were reviewed. Findings indicated that while women recognized the emotional changes in themselves after their childbirth, they were unable to perceive these as burdensome symptoms, resulting in delayed diagnosis of PND. The issues of cultures and traditions were perceived by Asian women as one of the contributing factors to PND.HCPs were regarded by the women as having a lack of knowledge in supporting mental wellbeing among postnatal women. Therefore, it is crucial to educate both HCPs and communities to notice and react to women’s depressed feelings. The management of maternal PND should acknowledge the social and cultural element as many women associated this with the development of PND.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".