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Record W7136034817 · doi:10.6084/m9.figshare.4534880

Additional file 1: of Emergency department presentations for atrial fibrillation and flutter in Alberta: a large population-based study

2017· article· W7136034817 on OpenAlexaboutno aff
Rhonda J. Rosychuk, Michelle Graham, Brian R. Holroyd, Brian Rowe

Bibliographic record

VenueFigshare · 2017
Typearticle
Language
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPercentilePopulationAtrial fibrillationEmergency departmentFiscal yearTriage

Abstract

fetched live from OpenAlex

Three additional tables and two additional figures. Table S1. Sex and age group directly standardized visit rates per 1,000 population (aged ≥ 35) by fiscal year and subsidy group. Table S2. Frequency and percentage (%) of ED* visits for AFF† by triage level for each fiscal year. Table S3. Duration of ED* visits for AFF† by disposition status and major geographic areas for patients (≥35 years). Median (Med), 25th percentile (25th) and 75th percentile (75th) are provided. Figure S1. Sex and age group directly standardized visit rates per 1,000 population by fiscal year and subsidy group for those aged 35–64: First Nations (∆), Government Sponsored Programs (+), Human Services Recipient (×), and Other (○). Figure S2. Sex and age group directly standardized visit rates per 1,000 population by fiscal year and subsidy group for seniors: First Nations (∆) and non-First Nations (○). (DOCX 310 kb)

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.431
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3520.018

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 head0.085
GPT teacher head0.371
Teacher spread0.286 · 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.

Study designObservational
Domainnot available
GenreDataset

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
Published2017
Admission routes1
Has abstractyes

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