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Record W2163925255 · doi:10.12968/ijpn.2008.14.4.29132

When advanced cancer patients won’t eat: family responses

2008· article· en· W2163925255 on OpenAlexaff
Susan McClement, Mike Harlos

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSt. Boniface HospitalWinnipeg Regional Health AuthorityUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsCancerMedicinePsychologyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

We conducted a grounded theory study examining nutritional care experiences in advanced cancer from the perspective of patients (n = 13), families (n = 23), and health care providers (n = 11) (McClement, 2001). That work generated an inductively derived model that captured important information about adult family members' perceptions and behaviour regarding the nutritional care their terminally ill adult relative received while hospitalized on an inpatient palliative care unit, and has been reported elsewhere (McClement et al, 2003). This article provides a more detailed description of one of the major sub-processes of the model regarding family member responses to declining oral intake and weight loss in a terminally ill relative-the sub-process of 'letting nature take its course: it's best not to eat.' The strategies family members use when letting nature take its course, and the consequences of these strategies for patients, family members and health care providers are reported. Implications for practice and research are provided.

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)0.007
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.138
GPT teacher head0.462
Teacher spread0.323 · 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 designQualitative
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

Citations33
Published2008
Admission routes1
Has abstractyes

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