MétaCan
Menu
Back to cohort
Record W2984928218 · doi:10.1001/amajethics.2019.988

What Are Good Guidelines for Evaluating Uterus Transplantation?

2019· article· en· W2984928218 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe AMA Journal of Ethic · 2019
Typearticle
Languageen
FieldMedicine
TopicOrgan and Tissue Transplantation Research
Canadian institutionsnot available
Fundersnot available
KeywordsInfertilityTransplantationUterusClinical PracticeGynecologyMedicineEthical issuesIntensive care medicineObstetricsEngineering ethicsPregnancyNursingSurgeryBiologyInternal medicineEngineering

Abstract

fetched live from OpenAlex

Recent advances in uterus transplantation (UTx) suggest it is on a trajectory toward becoming an accepted clinical practice to treat absolute uterine factor infertility (AUFI). Additional uses have been envisioned but not studied. UTx programs thus far have relied largely on ethical frameworks associated with clinical research, surgical innovation, organ transplantation, and assisted reproductive technologies, as reflected in the Revised Montreal Criteria and the Indianapolis Consensus. This article argues that it is time to develop integrated guidelines that incorporate existing evidence, acknowledge and address tensions among the ethical frameworks that have informed judgments of UTx for AUFI thus far, identify and address ethical questions on which existing frameworks are silent, and anticipate future ethical issues in UTx research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.238
GPT teacher head0.499
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it