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Record W1999096827 · doi:10.1080/15265161.2014.947442

Regulated Markets of Kidneys in Developed Countries or How to Increase Health Inequities

2014· letter· en· W1999096827 on OpenAlexaff
Julie Allard, Aviva Goldberg, Marie‐Chantal Fortin

Bibliographic record

VenueThe American Journal of Bioethics · 2014
Typeletter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity of Manitoba
Fundersnot available
KeywordsDeveloping countryMedicineDevelopment economicsPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

The article by Koplin (2014) presents a comprehensive review of existing empirical data on medical and psychological harms for kidney vendors in both legal and black-market systems. Based on this r...

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)0.021
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.154
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0080.017
Scholarly communication0.0120.011
Open science0.0040.006
Research integrity0.1540.072
Insufficient payload (model declined to judge)0.0140.003

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 head0.130
GPT teacher head0.461
Teacher spread0.332 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2014
Admission routes1
Has abstractno

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