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Record W2123691784 · doi:10.1177/104973202129120160

Evolving Routines: Preventing Fatigue Associated with Lung and Colorectal Cancer

2002· article· en· W2123691784 on OpenAlexaff
Kärin Olson, B. S. Tom, Joanne Hewitt, Joan Whittingham, Lisa Brown Buchanan, Gail Ganton

Bibliographic record

VenueQualitative Health Research · 2002
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsColorectal cancerCancer-related fatigueMedicineCancerLung cancerPsychologyClinical psychologyOncologyInternal medicine

Abstract

fetched live from OpenAlex

Some individuals with cancer develop fatigue whereas others do not. To begin the development of a biobehavioral model that could explain this phenomenon, the authors interviewed 29 individuals with lung and colorectal cancer before, during, and after treatment and obtained evaluable data for 18. Blood samples and body weight were obtained at the time of each interview. A three-stage process, evolving routines, and an adaptive behavioral mode labeled gliding characterized those who reported little or no fatigue, even when hemoglobin levels were low. Three other nonadaptive behavioral modes (inertia, disorganization, and overexertion) characterized those who reported fatigue. Individuals with similar disease and treatment profiles seldom demonstrated the same behavioral or biological response patterns.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.343
GPT teacher head0.543
Teacher spread0.201 · 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.

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

Citations20
Published2002
Admission routes1
Has abstractyes

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