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Record W71821049

Patient On-line Survey Results

2009· article· en· W71821049 on OpenAlexaboutno aff
Eric Blyth

Bibliographic record

VenueUniversity of Huddersfield Repository (University of Huddersfield) · 2009
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsFamily medicineMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

- Dr. Eric Blyth, University of Huddersfield \n \nDr. Blyth discussed the results of a 2008 on-line survey of CBRC patients and potential patients (60% of respondents were from Canada, 24% from Australia, 10% from the United States, and the remainder from Israel, the UK, and Greece). The survey, indicated that respondents were primarily recipients or potential recipients and that the majority of treatments undertaken (57%) involved egg donations. Conclusions of the survey included the need for more information about best practices, outcomes, and costs; better information and access to information by patients prior to their seeking treatment; and increased engagement by clinics in the home country. Dr. Blyth also provided information on a similar survey conducted in Britain by Infertility Network UK and compared the results to his own.

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)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.011

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 head0.031
GPT teacher head0.232
Teacher spread0.201 · 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 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

Citations0
Published2009
Admission routes1
Has abstractyes

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