Antenatal counselling for parents facing an extremely preterm birth: limitations of the medical evidence
Bibliographic record
Abstract
UNLABELLED: When physicians are asked for a consult for women in premature labour, they face a complex set of challenges. Policy statements recommend that women be given detailed information about the risks of various outcomes, including death, long-term disability and various specific neonatal problems. Both personal narratives and studies suggest that parents also base their decisions on factors other than the probabilistic facts about expected outcomes. Statistics are difficult to understand at any time. Rational decision-making may be difficult when taking life-and-death decisions. Furthermore, the role of emotions is not discussed in peri-viability guidelines. CONCLUSION: We argue against trying to tell parents every fact that we think might be relevant to their decision. This may be overwhelming for many parents. Instead, doctors should try to discern, on a case-by-case basis, what particular parents want and need. Information and delivery of information should be personalized. Unfortunately, evidence in this area is limited.
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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 | 0.102 | 0.439 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".