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Record W2090264949 · doi:10.1016/s0960-9776(13)70042-0

PO29 METASTATIC BREAST CANCER IN CANADA: THE LIVED EXPERIENCE OF PATIENTS AND CAREGIVERS PRESENTED BY THE CANADIAN BREAST CANCER NETWORK

2013· article· en· W2090264949 on OpenAlexaffabout
Niya Chari

Bibliographic record

VenueThe Breast · 2013
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsCanadian Breast Cancer Network
Fundersnot available
KeywordsMedicineBreast cancerMetastatic breast cancerCancerOncologyInternal medicine

Abstract

fetched live from OpenAlex

Abstracts / The Breast 22 S3 (2013) S19-S63support from (where applicable) their spouse (89% vs 78% without a caregiver), parents (90% vs 84% without a caregiver), and co-workers (79% vs 70% without a caregiver).Compared with those who did not have a caregiver, women who had a caregiver were also more likely to be satisfied with the social support they received from family and friends (83% vs 71% without a caregiver).Conclusions: Addressing the emotional and QOL concerns of women with ABC is critical to their overall well-being and health.Resources and sources of support for these concerns are needed for not only those living with ABC but also family members, caregivers, and members of a support network.PO28

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.003
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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 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

Citations1
Published2013
Admission routes2
Has abstractno

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