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QUALITY IMPROVEMENTS- EVALUATION OF KEY PERFORMANCE INDICATORS FOR STROKE STUDIES CONDUCTED AT A LARGE TEACHING HOSPITAL OVER 3 YEARS

2017· other· en· W6908559820 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
FieldSocial Sciences
TopicHistorical and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Quality (philosophy)Performance indicatorQuality managementHealth services researchKey (lock)Acute strokeTeaching hospital

Abstract

fetched live from OpenAlex

The Hamilton General Hospital is a regional stroke centre located in Ontario, Canada which services 2.2 million Canadians over 11, 945 km2. Over the past 5 years, our stroke research program has undergone a rapid increase in clinical research activities across the continuum of stroke care from hyper acute stroke to rehabilitation. The research team has expanded to include seven research coordinators/nurses with diverse clinical research skillsets. After this period of rapid expansion we undertook a quality improvement (QI) process to evaluate our performance across key quality indicators. Through evaluating studies conducted over the past three years, we identified studies that over-achieved in these important measures of quality. We aimed to identify the underlying factors driving these achievements so that we may integrate these measures into all future studies.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0000.004
Open science0.0030.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.167
GPT teacher head0.444
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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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