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Record W3183288317 · doi:10.1002/wmh3.469

Access to genetic testing for rare diseases: Existing gaps in public‐facing information

2021· article· en· W3183288317 on OpenAlex
Julie M. Robillard, Tanya L. Feng, Katarzyna Kabacińska

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWorld Medical & Health Policy · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsGenetic testingReimbursementContext (archaeology)CLARITYPublic healthMedicineGovernment (linguistics)Rare diseaseHealth careBusinessPublic policyDiseaseInternet privacyPublic relationsPolitical scienceEconomic growthNursingPathologyComputer scienceEconomics

Abstract

fetched live from OpenAlex

Genetic testing plays an increasingly important role in the diagnosis and potential treatment of inherited and rare conditions, such as aniridia-a disease that leads to abnormal eye development, as well as in health research on these conditions. As genetic testing is increasingly sought for accurate and early diagnosis of rare genetic disorders and in the context of direct-to-consumer genomics, it is critical to examine the public-facing information about access to these services and reimbursement policies. We conducted a targeted policy and public-facing resource search. Our analysis of resources available for the patient community revealed that there is very little practical guidance available about access and reimbursement for genetic testing for rare diseases. Greater clarity in public-facing resources about genetic testing would be beneficial to the patient community as it would promote informed choices about the procedure, mitigate potential harms associated with lack of information and enable patient engagement in their own health care.

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.

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)0.000
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.420
Teacher spread0.362 · 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