Canadian maternity, newborn, and women's health nursing : comprehensive care across the lifespan
Bibliographic record
Abstract
Unit 1: FOUNDATIONS OF MATERNAL, NEWBORN, AND WOMEN'S HEALTH CARE Chapter 1: Philosophy and Framework for Women's Reproductive and Sexual Health Chapter 2: Health Promotion Chapter 3: Nutrition for Adolescent and Adult Women Chapter 4: Medical Alterations in Women During Adolescence and Adulthood Chapter 5: Mental Health Concerns for Women in Adolescence and Adulthood Chapter 6: Sexuality and Reproduction Chapter 7: Family Formation Unit 2: SPECIAL REPRODUCTIVE AND HEALTH CONCERNS Chapter 8: Fertility Control and Contraception Chapter 9: Voluntary Pregnancy Termination Chapter 10: Fertility Challenges Chapter 11: Genetics, Embryology, and Preconceptual/Prenatal Assessment and Screening Unit 3: PREGNANCY Chapter 12: Process of Pregnancy Chapter 13: High-Risk Pregnancy Chapter 14: Educational Preparation for Pregnancy, Childbirth, and Parenthood Unit 4: LABOUR AND CHILDBIRTH Chapter 15: Labour and Childbirth Chapter 16: High-Risk Labor and Childbirth Chapter 17: Pharmacologic Pain Management of Labour Unit 5: POSTPARTUM PERIOD AND NEWBORN CARE Chapter 18: Fourth Stage of Labour and Postpartum Period Chapter 19: The High-Risk Postpartum Woman Chapter 20: The Healthy Newborn Chapter 21: Newborn Nutrition Chapter 22: The High-Risk Newborn Unit 6: MENOPAUSE AND BEYOND Chapter 23: The Menopausal Experience Chapter 24: The Older Postmenopausal Woman
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".