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Record W2530586285 · doi:10.3389/fonc.2016.00215

The MRI-Linear Accelerator Consortium: Evidence-Based Clinical Introduction of an Innovation in Radiation Oncology Connecting Researchers, Methodology, Data Collection, Quality Assurance, and Technical Development

2016· article· en· W2530586285 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Oncology · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsSunnybrook Hospital
FundersMedical Research CouncilUniversitair Medisch Centrum UtrechtNational Institute for Health and Care ResearchInstitute of Cancer ResearchCancer Research UKMedical College of WisconsinUniversity of Texas MD Anderson Cancer CenterElektaCentral Manchester University Hospitals NHS Foundation Trust
KeywordsQuality assuranceMedical physicsRadiation oncologyMedicineClinical OncologyComputer scienceRadiation therapyInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

An international research consortium has been formed to facilitate evidence-based introduction of MR-guided radiotherapy (MR-linac) and to address how the MR-linac could be used to achieve an optimized radiation treatment approach to improve patients' survival, local, and regional tumor control and quality of life. The present paper describes the organizational structure of the clinical part of the MR-linac consortium. Furthermore, it elucidates why collaboration on this large project is necessary, and how a central data registry program will be implemented.

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.

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)0.014
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.616
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.261
GPT teacher head0.512
Teacher spread0.251 · 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