MétaCan
Menu
Back to cohort
Record W2131241212 · doi:10.1586/erp.12.50

A ‘year in the life’ of health services research in oncology

2012· review· en· W2131241212 on OpenAlexaff
Michael Brundage, Claire Snyder, Brenda Bass

Bibliographic record

VenueExpert Review of Pharmacoeconomics & Outcomes Research · 2012
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineHealth careMEDLINEFamily medicineOncologyNursingPolitical science

Abstract

fetched live from OpenAlex

Oncology health services research (HSR) is a broad, multidimensional field. Current areas of research foci may be informative. We searched Medline for oncology HSR papers published in English in a single year (2009). Abstracted data related to access, quality, cost, health/wellbeing, place on the cancer continuum and study design. Among 1113 papers, the most commonly studied HSR domain was quality-of-care (65%). Within the care continuum, 'treatment' received the greatest attention (37%), and 'prevention' the least (5%). More specifically, treatment-related quality-of-care was most often studied (23%). Breast cancer was the most common site focus (28%). Most studies were descriptive (75%), retrospective (35%) or cross-sectional (35%). These findings might inform the decisions of researchers or policy makers seeking to improve cancer health services delivery.

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)0.047
metaresearch head score (Gemma)0.102
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 score0.047
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0130.023
Science and technology studies0.0020.005
Scholarly communication0.0120.016
Open science0.0020.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0100.002

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 head0.250
GPT teacher head0.594
Teacher spread0.344 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueExpert Review of Pharmacoeconomics & Outcomes ResearchSame topicEconomic and Financial Impacts of CancerFrench-language works237,207