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Record W6949970047 · doi:10.5281/zenodo.5636321

Description of rare genetic variants for long QT syndrome identified from a population-based study

2021· preprint· en· W6949970047 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typepreprint
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsGenetic variantsResearch ethicsEthics committeeGenetic counselingCluster (spacecraft)Compliance (psychology)Informed consentPreprint

Abstract

fetched live from OpenAlex

Preprint "Description of rare genetic variants for long QT syndrome identified from a population-based study" Disclaimer: These datasets were generated during the course of academic research conducted at the Faculty of Medicine, The Chinese University of Hong Kong, which received ethics approval by The Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee of the Hospital Authority. They have been anonymised and are deposited for further advancement of medical research in full compliance with University Regulations and Policy on Dataset Deposit and Sharing. For additional information: https://libguides.lib.cuhk.edu.hk/RDM/dataset_deposit Access is permitted for research purposes only. The use of these datasets should provide acknowledgements of such efforts by citing this DOI.

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)0.002
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0490.010

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 head0.038
GPT teacher head0.266
Teacher spread0.228 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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