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Record W2398784408 · doi:10.1111/ctr.12767

What information about donation after circulatory death is available on the Internet for potential donor families?

2016· article· en· W2398784408 on OpenAlexaff
Kristin A. Black, Katherine Miller, Gavin Beck, Mike Moser

Bibliographic record

VenueClinical Transplantation · 2016
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDonationMedicineThe InternetWeb pageOrgan donationMedical informationInternet privacyTone (literature)Family medicineAdvertisingMedical emergencySurgeryWorld Wide WebTransplantationComputer scienceLaw

Abstract

fetched live from OpenAlex

INTRODUCTION: The purpose of this study is to determine what information about donation after circulatory death (DCD) is available on the Internet and to document the common statements for and against DCD. METHODS: The search terms non-heart-beating donor, donation after cardiac death, DCD, deceased donor, organ donation, and organ harvesting were entered into the four most-accessed English-language Internet search engines. The top 10 webpages from each search (240 webpages) yielded 116 unique sites. Three reviewers reviewed each webpage and recorded statements for and against DCD as well as site type, tone, and mention of DCD. RESULTS: While 59 (50.9%) of the overall 116 sites included DCD information, only 10% of sites found with the term "organ donation" mentioned DCD at all. The sites that did include DCD were mostly (78%) of the type "medical journal" or "hospital or university webpage" and 89% of these had a positive or neutral tone. Nine positive and nine negative tropes were defined using the Grounded Theory Method. CONCLUSION: This study reveals the lack of information regarding DCD in organ donation webpages. Thoughtful responses to these statements should be considered in family discussions and in the design of future webpages.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.315
Teacher spread0.273 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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