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Adaptation of Consultation Planning for Native American and Latina Women With Breast Cancer

2009· article· en· W2056041302 on OpenAlex
Jeffrey Belkora, Lauren Franklin, Sara O’Donnell, Julie Ohnemus, Dawn Stacey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Rural Health · 2009
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFamily medicineMedicineAdaptation (eye)Native americanBreast cancerResource (disambiguation)African americanGerontologyPsychologyCancerSociologyComputer science

Abstract

fetched live from OpenAlex

CONTEXT: Resource centers in rural, underserved areas are implementing Consultation Planning (CP) to help women with breast cancer create a question list before a doctor visit. PURPOSE: To identify changes needed for acceptable delivery of CP to rural Native Americans and Latinas. METHODS: We interviewed and surveyed 27 Native American and Latino key informants. We coded interviews thematically, and calculated summary statistics for the survey data. FINDINGS: Native American and Latino respondents endorsed CP as culturally acceptable to their communities, while suggesting changes. Respondents also raised the topic of how to further support patients once they have successfully prepared a question list using CP. CONCLUSIONS: The resource centers implemented the requested changes.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.100

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)0.0000.000

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 head0.056
GPT teacher head0.391
Teacher spread0.334 · 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