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Storytelling

2004· article· en· W2327617102 on OpenAlexaff
Carolyn Hope Smeltzer, Fran Vlasses

Bibliographic record

VenueJournal of Nursing Care Quality · 2004
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsStorytellingComputer scienceNarrativeLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

From the Management Consulting Services, PricewaterhouseCoopers LLP, Chicago, Ill, Advocate Health System in Oakbrook, Ill, and Sisters of Charity Leavenworth Health System, Leneca, Kan (Smeltzer) The Marcella Niehoff School of Nursing, Loyola University Chicago, Chicago, Ill. (Vlasses) Corresponding author: Carolyn Hope Smeltzer, EdD, RN, FAAN, FACHE, Management Consulting Services, PricewaterhouseCoopers LLP, One North Wacker, Chicago, IL 60606 (e-mail: [email protected]). *Carolyn Smeltzer and Fran Vlasses have created a coffee table book on the stories of nurses with photographs that illustrate the nurses' stories and their lives. Ordinary People, Extraordinary Lives, The Stories of Nurses is available through Sigma Theta Tau International (www.nursingsociety.org/publications).

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.112
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1120.022

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 head0.181
GPT teacher head0.527
Teacher spread0.346 · 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 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

Citations12
Published2004
Admission routes1
Has abstractyes

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