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Record W2171502866 · doi:10.5737/1181912x1011421

Cancer treatmentinduced menopause: Meaning for breast and gynecological cancer survivors

2000· article· en· W2171502866 on OpenAlexaffvenue
Christine S. Davis, Jeanie E. Zinkand, Margaret I. Fitch

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2000
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsWilliam Osler Health SystemSunnybrook Health Science Centre
Fundersnot available
KeywordsMenopauseDistressCoping (psychology)Breast cancerPsychosocialMedicineCancerContext (archaeology)Survivorship curveGynecologyClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Many cancer survivors are faced with irreversible changes resulting from cancer treatment. One such change some women face after cancer is treatment-induced menopause. Eight women (four with breast and four with gynecological cancers) were interviewed to explore the impact of treatment-induced menopause on their lives. Results indicated that participants' understanding and coping with menopause occurred within the larger context of the total cancer experience. For some of the women, menopause was not a significant problem; for others, the symptoms caused major distress and were a continuing reminder of the losses suffered due to cancer. Important concerns for all participants were: taking and keeping control, the desire to return to "normal" after cancer, and maintaining a coherent sense of self. Strong statements were also made about the power of knowing and the power of support in coping with treatment-induced menopause. Findings are discussed with implications for nursing practice.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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 designObservational
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

Citations22
Published2000
Admission routes2
Has abstractyes

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