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Record W2191471066 · doi:10.3233/blc-150021

Bladder Cancer Patient Advocacy: A Global Perspective

2015· review· en· W2191471066 on OpenAlexaboutno aff
Diane Zipursky Quale, Rick Bangs, Monica Smith, David Guttman, Tammy Northam, Andrew Winterbottom, Andrea Necchi, Edoardo Fiorini, Stephanie Demkiw

Bibliographic record

VenueBladder Cancer · 2015
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsBladder cancerGlobePatient advocacyMedicinePublic relationsPolitical scienceNon profitPerspective (graphical)CancerNursingFamily medicineMEDLINEPublic administrationInternal medicine

Abstract

fetched live from OpenAlex

Over the past 20 years, cancer patient advocacy groups have demonstrated that patient engagement in cancer care is essential to improving patient quality of life and outcomes. Bladder cancer patient advocacy only began 10 years ago in the United States, but is now expanding around the globe with non-profit organizations established in Canada, the United Kingdom and Italy, and efforts underway in Australia. These organizations, at different levels of maturity, are raising awareness of bladder cancer and providing essential information and resources to bladder cancer patients and their families. The patient advocacy organizations are also helping to advance research efforts by funding research proposals and facilitating research collaborations. Strong partnerships between these patient advocates and the bladder cancer medical community are essential to ensuringsustainability for these advocacy organizations, increasing funding to support advances in bladder cancer treatment, and improving patient outcomes.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0060.006
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 head0.079
GPT teacher head0.420
Teacher spread0.342 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2015
Admission routes1
Has abstractyes

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