MétaCan
Menu
Back to cohort
Record W4211119384 · doi:10.1016/j.ijrobp.2022.01.053

Is Clinical Research Serving the Needs of the Global Cancer Burden? An Analysis of Contemporary Global Radiation Therapy Randomized Controlled Trials

2022· article· en· W4211119384 on OpenAlexaff
Joanna Dodkins, Wilma M. Hopman, J. Connor Wells, Yolande Lievens, Rozita Abdul Malik, C.S. Pramesh, Bishal Gyawali, Nazik Hammad, Deborah Mukherji, Richard Sullivan, Jeannette Parkes, Christopher M. Booth, Ajay Aggarwal

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2022
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsQueen's University
FundersScience and Technology Facilities CouncilInternational Atomic Energy AgencyCancer Research UKMedical Research CouncilNational Institute for Health and Care ResearchAustralian Government
KeywordsMedicineRandomized controlled trialRadiation therapySystemic therapyCohortClinical endpointCancerBreast cancerInternal medicineFamily medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.144
metaresearch head score (Gemma)0.235
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1440.235
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.013
Bibliometrics0.0020.005
Science and technology studies0.0010.005
Scholarly communication0.0060.005
Open science0.0020.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.106
GPT teacher head0.523
Teacher spread0.417 · 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 designObservational
DomainMethods
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

Citations32
Published2022
Admission routes1
Has abstractno

Explore more

Same venueInternational Journal of Radiation Oncology*Biology*PhysicsSame topicAdvances in Oncology and RadiotherapyFrench-language works237,207