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Record W4389287341 · doi:10.1016/j.clon.2023.11.041

Prospective Longitudinal Assessment of Quality of Life After Stereotactic Ablative Radiotherapy for Oligometastases: Analysis of the Population-based SABR-5 Phase II Trial

2023· article· en· W4389287341 on OpenAlexaff
Ella Mae Cruz-Lim, Benjamin Mou, Sarah Baker, G. Arbour, Kelsey Stefanyk, W. Jiang, Mitchell Liu, Alanah Bergman, Devin Schellenberg, Abraham Alexander, Tanya Berrang, Andrew Bang, N. Chng, Quinn Matthews, Hannah Carolan, F. Hsu, S. Miller, Siavash Atrchian, Elaine Chan, Clement Ho, Islam Mohamed, Angela Lin, V. Huang, Ante Mestrovic, Derek Hyde, C. Lund, Howard Pai, Boris Valev, Shilo Lefresne, Scott Tyldesley, Robert Olson

Bibliographic record

VenueClinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of Northern British ColumbiaAbbotsford Veterinary ClinicColumbia Bible CollegeUniversity of VictoriaKelowna General HospitalBC Cancer AgencyUniversity of British ColumbiaSurrey Memorial HospitalPositive Living NorthUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsMedicineSABR volatility modelQuality of life (healthcare)PopulationRadiation therapyMinimal clinically important differenceBrief Pain InventoryProspective cohort studySurgeryPhysical therapyRandomized controlled trialChronic pain

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.180
GPT teacher head0.545
Teacher spread0.365 · 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 designNon-randomized trial
Domainnot available
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

Citations6
Published2023
Admission routes1
Has abstractno

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