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Record W2959290289 · doi:10.3389/fped.2019.00312

Principlism and Personalism. Comparing Two Ethical Models Applied Clinically in Neonates Undergoing Extracorporeal Membrane Oxygenation Support

2019· review· en· W2959290289 on OpenAlexaffabout
Matteo Di Nardo, Anna Dalle Ore, Giuseppina Testa, Gail M. Annich, Edoardo Piervincenzi, Giorgio Zampini, Gabriella Bottari, Corrado Cecchetti, Antonio Amodeo, Roberto Lorusso, Lorenzo Del Sorbo, Roxanne Kirsch

Bibliographic record

VenueFrontiers in Pediatrics · 2019
Typereview
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsToronto General HospitalUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsPersonalismExtracorporeal membrane oxygenationMedicineExtracorporealOxygenationIntensive care medicineAnesthesiaSurgeryEpistemology

Abstract

fetched live from OpenAlex

Extracorporeal membrane oxygenation (ECMO) is a technology used to temporarily assist critically ill patients with acute and reversible life-threatening cardiac and/or respiratory failure. This technology can often be lifesaving but is also associated with several complications that may contribute to reduced survival. Currently, neonates supported with ECMO are complex and bear an increased risk of mortality. This means that clinicians must be particularly prepared not only to deal with complex clinical scenarios, but also ethical issues associated with ECMO. In particular, clinicians should be trained to handle unsuccessful ECMO runs with attention to high quality end of life care. Within this manuscript we will compare and contrast the application of two ethical frameworks, used in the authors' institutions (Toronto and Rome). This is intended to enhance a broader understanding of cultural differences in applied ethics which is useful to the clinician in an increasingly multicultural and diverse patient mix.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.006
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.116
GPT teacher head0.408
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2019
Admission routes2
Has abstractyes

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