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Record W4392706750 · doi:10.3390/curroncol31030111

Overview of the Engagement Process to Develop the Future of Cancer Impact (FOCI) Report in Alberta: The Power of Collective Action

2024· article· en· W4392706750 on OpenAlexaffvenueabout
Anna Pujadas Botey, Tara R. Bond, Eliya Farah, Chantelle Carbonell, Stacey Dyck, Angela Estey, Douglas A. Stewart, Darren R. Brenner, Paula J. Robson

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of CalgaryAlberta HealthUniversity of AlbertaAlberta Health Services
Fundersnot available
KeywordsStakeholder engagementStakeholderProcess (computing)Health careAction (physics)Collective actionPublic relationsMedicineEngineering ethicsPolitical scienceKnowledge managementProcess managementBusinessComputer scienceEngineeringPolitics

Abstract

fetched live from OpenAlex

This commentary provides a detailed overview of the extensive stakeholder engagement efforts critical to the development of the Future of Cancer Impact (FOCI) in Alberta report. The overarching aim of the FOCI report was to support informed and strategic discussions and actions that will help key stakeholders in the province prepare for a future with increasing cancer incidence and survival. Employing a comprehensive approach and a diverse range of engagement activities, insights from a wide spectrum of stakeholders were gathered and subsequently used to shape the content of the report. This inclusive process ensured broad representation of perspectives, contributing to a deeper understanding of the complexities in cancer care. The outcome is a robust, consensus-driven report with recommendations set to drive significant transformations within the healthcare system. These efforts highlight the critical role of extensive, inclusive, and collaborative engagement in shaping healthcare initiatives and advancing discussions crucial for the future of cancer care in Alberta.

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)0.066
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0180.009
Scholarly communication0.0120.002
Open science0.0040.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.699
GPT teacher head0.745
Teacher spread0.046 · 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.

Study designQualitative
DomainEvaluation
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

Citations0
Published2024
Admission routes3
Has abstractyes

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