Considering the Developing Entity in an Artificial Womb as a Patient
Bibliographic record
Abstract
Artificial womb (AW) prototypes are currently being developed with the aim of improving the medical care of extremely premature infants. Despite the seemingly imminent reality of partial ectogenesis (i.e., gestation partially outside a human womb), there is persisting debate about the moral status of the fetus transferred in an AW-henceforth, the "developing entity." For some, AWs are simply another neonatal intensive cares' technology. Thus, developing entities in AWs should deserve the same protections as newborns in incubators. Others consider that AWs are fundamentally different technologies than incubators. Therefore, they believe that developing entities in AWs are new moral entities. These differences in perception generate disagreement about how developing entities in AWs should be treated and how decisions about them should be made. We argue that developing entities in AWs should be considered patients by transposing Chervenak and McCullough's "The fetus as a patient" proposition to the context of partial ectogenesis. As pregnant persons will have to consent to transfer their fetuses in AWs, and this technology will ultimately present itself as a beneficial medical intervention for viable developing entities in AWs, these latter would be patients, even if they are not legally and morally recognized as person. Thus, the moral obligations of beneficence and non-maleficence owed by physicians to their patients would apply to entities in AWs, ethically guiding their treatment and decision-making toward them.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.049 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".