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Holding

2012· article· en· W4241643429 on OpenAlexaff
Veneta Masson

Bibliographic record

VenueAJN American Journal of Nursing · 2012
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsCARE Canada
Fundersnot available
KeywordsFoleyPoetryChapelArtPsychologyNursingSociologyArt historyMedicineLiterature

Abstract

fetched live from OpenAlex

Veneta Masson is a nurse and writer living in Washington, DC. After a long career in practice, most recently as a family NP, she's now teaching health care ethics online and on campus at Georgetown University, also in Washington. She says, “The inspiration for this poem came out of two uncannily similar experiences I had as a family caregiver, several years apart, in both of which I took refuge in the chapel at the same hospital. It's not at all the poem I thought I would write. It is, however, a poem that had something important to teach me.” “Holding” © 2012 by Veneta Masson. Contact author: [email protected]. Art of Nursing is coordinated by Sylvia Foley, senior editor: [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 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)0.000
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.217
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.2170.051

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 head0.051
GPT teacher head0.371
Teacher spread0.320 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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