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Record W2560534345 · doi:10.1002/pon.4272

Abstracts

2016· article· en· W2560534345 on OpenAlexaboutno aff

Bibliographic record

VenuePsycho-Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
FundersAutoritatea Natională pentru Cercetare StiintificăPublic Health AgencyMacmillan Cancer Support
KeywordsDistressAttendanceStressorPsychological distressEthnic groupPublic healthDeveloped country

Abstract

fetched live from OpenAlex

Aboriginal peoples have been and continue to be subjected to multiple traumas and stressors that contribute to their greater risk for a variety of health and social problems. Among these health issues, cancer has been identified as the third leading cause of death in the First Nations population, and survival rates are lower because many are not diagnosed until it is too late. Due to the high prevalence and mortality rates of cancer, its diagnosis and treatment commonly evoke extreme psychological distress that can have significant implications for treatment and recovery. Having a greater understanding of risk factors that contribute to individual differences in psychological responses to cancer will help identify vulnerable populations and facilitate the development of culturally appropriate interventions. The present study assessed how familial Indian Residential School (IRS) attendance is linked with psychological distress among those with and without cancer in a representative sample of First Nations adults living on-reserve. Statistical analyses were carried out using data from the 2008-10 First Nations Regional Heath Survey (RHS), a representative survey of 4,934 First Nations living on-reserve from across Canada (excluding Nunavut).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.002

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 head0.034
GPT teacher head0.371
Teacher spread0.337 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations11
Published2016
Admission routes1
Has abstractyes

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