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Record W1963818892 · doi:10.1136/jme.2009.034306

The cost of autonomy: estimates from recent advances in living donor kidney transplantation

2010· article· en· W1963818892 on OpenAlexafffund
Phedias Diamandis

Bibliographic record

VenueJournal of Medical Ethics · 2010
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsAutonomyDonationHealth careOrgan donationPublic relationsTransplantationQuality of life (healthcare)Resource (disambiguation)PsychologyMedicinePolitical scienceNursingLawComputer scienceSurgery

Abstract

fetched live from OpenAlex

Autonomy, an individual's right to make personal decisions regarding his/her own health, represents one of the major ethical principles of medicine. While there are many examples citing the benefits this right provides for the individual, the impact that personal healthcare decisions have on others is often neglected. Here, evidence from end-stage renal disease is reviewed to hypothesise the creation of a universal kidney donation programme that although provides unparalleled benefits to its citizens, relies on the participation of a large proportion of the society. Given that this essay also addresses the public's major concerns regarding kidney donation, one of the only remaining implementation barriers is the individuals' right not to participate. Therefore, irrespective of the humane and complex emotionally laden reasons for not enrolling in such programmes, this essay provides some estimates of the significant resource and quality of life costs associated with autonomy. Assuming humans are competent to make informed personal healthcare choices, similar to recent efforts to increase awareness about the negative impact of certain lifestyle choices on global warming, citizens should also be better informed about the medical costs their autonomy has on society.

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 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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
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 integrity0.0000.002
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 head0.023
GPT teacher head0.357
Teacher spread0.333 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2010
Admission routes2
Has abstractyes

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