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Record W2082459525 · doi:10.1016/j.jbo.2012.12.003

‘Who’, ‘when’ and ‘how’ in re-irradiation of recurrent painful bone metastases

2013· review· en· W2082459525 on OpenAlex
Florence Mok, Kenneth Li, Rebecca M.W. Yeung, Kam-Hung Wong, Brian Yu, Erin Wong, Gillian Bedard, Edward Chow

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

VenueJournal of bone oncology · 2013
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
FundersOfelia Cancer Research FundMichael and Karyn Goldstein Cancer Research FundJoseph and Silvana Melara Cancer Research Fund
KeywordsMedicineRadiation therapyIrradiationPain reliefRandomized controlled trialClinical trialSurgeryBone metastasisMetastasisCancerInternal medicine

Abstract

fetched live from OpenAlex

Re-irradiation of painful bony metastases is increasingly performed since patients are receiving better systemic treatments and having longer life expectancy, and may also be due to the increase use of initial single fraction radiotherapy. However, randomized control trial on the efficacy of re-irradiation is lacking. A recent meta-analysis concluded with a 58% response rate for pain relief by re-irradiation of symptomatic bone metastases. In this review, the effectiveness of re-irradiation in terms of clinical and economical aspects, and clinical questions on who, when, and how to re-irradiate would be discussed. A brief review of other treatment options and comparison with re-irradiation of bone metastases would be performed.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.391
Teacher spread0.303 · 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