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Record W3123392454 · doi:10.1016/j.ijrobp.2020.11.021

Stereotactic Body Radiation Therapy for Spinal Metastases: Tumor Control Probability Analyses and Recommended Reporting Standards

2021· review· en· W3123392454 on OpenAlexaff
Scott G. Soltys, Jimm Grimm, Michael T. Milano, Jinyu Xue, Arjun Sahgal, Ellen Yorke, Yoshiya Yamada, G Ding, X. Allen Li, D. Michael Lovelock, Andrew Jackson, Lijun Ma, Issam El Naqa, Iris C. Gibbs, Lawrence B. Marks, Stanley Benedict

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2021
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Cancer InstituteNational Institutes of HealthNovocureElektaSiemens USA
KeywordsMedicineRadiation therapyMedical physicsRadiologyNuclear 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)0.035
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.054
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0090.006
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0070.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.002

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 head0.124
GPT teacher head0.480
Teacher spread0.355 · 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 designNot applicable
DomainReporting
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

Citations54
Published2021
Admission routes1
Has abstractno

Explore more

Same venueInternational Journal of Radiation Oncology*Biology*PhysicsSame topicManagement of metastatic bone diseaseFrench-language works237,207