MétaCan
Menu
Back to cohort
Record W2126751853 · doi:10.5737/1181912x243166168

Rethinking assumptions about cancer survivorship

2014· article· en· W2126751853 on OpenAlexafffundvenueabout
Svetlana Ristovski‐Slijepcevic, Kirsten Bell

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsSurvivorship curveCancer survivorshipPerspective (graphical)DisciplineCancer survivorNursing researchSociologyCancerPsychologyMedicineSocial scienceNursingComputer science

Abstract

fetched live from OpenAlex

A growing body of research informed by theories and methods in the social sciences and humanities indicates that certain problematic messages are commonly embedded in popular and oncological representations of cancer. Becoming more aware of these underlying messages has the potential to improve the ways clinicians think about and manage cancer. (Note: A written response to this article appears in Truant, Kohli, & Stephens (2014), Response to "Rethinking Assumptions about Cancer Survivorship": A Nursing Disciplinary Perspective, Canadian Oncology Nursing Journal, Vol. 24, Issue 3, p. 169).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.344
Teacher spread0.302 · 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
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

Citations9
Published2014
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Oncology Nursing JournalSame topicCancer survivorship and careFrench-language works237,207