MétaCan
Menu
Back to cohort
Record W2603164836 · doi:10.3399/bjgpopen17x100665

Aortic valve surgery: how reliable are health information websites?

2017· article· en· W2603164836 on OpenAlexaff
Ming Yi Lai, Hilary McDermott, John B. Chambers

Bibliographic record

VenueBJGP Open · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsThe InternetAortic valve replacementMedicineCardiac surgeryAortic valveSurgeryInternal medicineWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Aortic valve replacement is one of the most common cardiac operations currently performed. Patients increasingly use the internet for information about their diagnosis and it would therefore be important to know how reliable this is. AIM: To determine the reliability of internet information on aortic valve replacement surgery. DESIGN & SETTING: This was a web-based project scoring sites that might be accessed by a patient. METHOD: The first 50 websites found on each of the four most popular search engines in the UK were viewed, as well as the first 50 videos found on the most popular video-host website. Eligible websites were assessed according to seven positive criteria and three negative criteria, giving a possible range of scores from -6 to 14. RESULTS: There were 79 sites and the median score was 5 (range -1 to 14). There were statistically significant differences between organisation/educational sites with score 7 (2 to 14), hospital sites with score 2 (-1 to 10), commercial sites with score 2.5 (0 to 9) and videos with score 5 (2 to 11). The highest scores went to three NHS sites (score 13 or 14), .gov sites (median score 8.5) and Health On the Net Foundation (HON) accredited sites (median score 7). CONCLUSION: Information on the internet about aortic valve replacement is variable but NHS sites provide the most reliable information.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0010.014
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.004

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 head0.133
GPT teacher head0.483
Teacher spread0.350 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBJGP OpenSame topicHealth Literacy and Information AccessibilityFrench-language works237,207