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Record W2324759444 · doi:10.1097/ncm.0b013e3181e264d1

What Is the Formula That Adds Up to Heart Failure Success?

2010· article· en· W2324759444 on OpenAlexaff
Sheila Shelley, Brenda Vollmar

Bibliographic record

VenueProfessional Case Management · 2010
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsRegistered Nurses' Association of Ontario
Fundersnot available
KeywordsNursingRegistered nurseCertificationMedicineRehabilitationManagementPhysical therapy

Abstract

fetched live from OpenAlex

Sheila Shelley, RN, BSN, is a registered nurse at Winchester Hospital. Here she has worked as a staff nurse, outpatient heart failure nurse, and home care nurse as well as participating in Nursing Research Council and Cardiac Care Team. Brenda Vollmar, RN, CRRN, is a registered nurse, certified in Rehabilitation Nursing. Brenda has been employed as a staff nurse for Winchester Hospital's Home Care for the last 14 years. She participated in the planning and development of the Outpatient Heart Failure Program and is a member of the Nursing Research Council. Address correspondence to Winchester Hospital, 112 Ballard St., Tewksbury MA 01876 ([email protected]).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.329
Teacher spread0.306 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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