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Record W2084390634 · doi:10.1002/cncr.27464

A prospective model of care for breast cancer rehabilitation: Function

2012· review· en· W2084390634 on OpenAlexaff
Kristin L. Campbell, Andrea L. Pusic, David S. Zucker, Margaret L. McNeely, Jill Binkley, Andrea Cheville, Kenneth J. Harwood

Bibliographic record

VenueCancer · 2012
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsAlberta Cancer FoundationUniversity of AlbertaUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsBreast cancerMedicineQuality of life (healthcare)RehabilitationContext (archaeology)CancerPsychological interventionGerontologyProspective cohort studyPhysical therapyNursingInternal medicine

Abstract

fetched live from OpenAlex

A significant proportion of adult breast cancer survivors experience deficits in function and restriction in participation in life roles that may remain many years after diagnosis. Function is a complex construct that takes into account the interactions between an individual, their health condition, and the social and personal context in which they live. Research to date on limitations in activities of daily living, upper extremity function, and functional capacity in breast cancer survivors illustrates the need for prospective measurement of function using measures that are sensitive to the unique issues of breast cancer survivors and the need for the development of effective rehabilitation interventions to improve function. Limitations in function have a significant impact on quality of life, but less is known about the implications on return to work and survival, as well as the impact of other comorbidities and aging on the function limitations in breast cancer survivors. This review provides a rationale for the integration of measures of function into breast cancer care to more fully appreciate the functional limitations associated with breast cancer diagnosis and treatment and to aid in the development of better rehabilitation care for breast cancer survivors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.364
Teacher spread0.316 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations114
Published2012
Admission routes1
Has abstractyes

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