A transdisciplinary approach to the decision-making process in extreme prematurity
Bibliographic record
Abstract
BACKGROUND: A wide range of dilemmas encountered in the health domain can be addressed more efficiently by a transdisciplinary approach. The complex context of extreme prematurity, which is raising important challenges for caregivers and parents, warrants such an approach. METHODS: In the present work, experts from various disciplinary fields, namely biomedical, epidemiology, psychology, ethics, and law, were enrolled to participate in a reflection. Gathering a group of experts could be very demanding, both in terms of time and resources, so we created a web-based discussion forum to facilitate the exchanges. The participants were mandated to solve two questions: "Which parameters should be considered before delivering survival care to a premature baby born at the threshold of viability?" and "Would it be acceptable to give different information to parents according to the sex of the baby considering that outcome differences exist between sexes?" RESULTS: The discussion forum was performed over a period of nine months and went through three phases: unidisciplinary, interdisciplinary and transdisciplinary, which required extensive discussions and the preparation of several written reports. Those steps were successfully achieved and the participants finally developed a consensual point of view regarding the initial questions. This discussion board also led to a concrete knowledge product, the publication of the popularized results as an electronic book. CONCLUSIONS: We propose, with our transdisciplinary analysis, a relevant and innovative complement to existing guidelines regarding the decision-making process for premature infants born at the threshold of viability, with an emphasis on the respective responsabilities of the caregivers and the parents.
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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 | 0.042 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".