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Record W1488618428 · doi:10.3747/co.v13i6.108

How Should We Describe the Benefits of Palliative Radiotherapy?

2006· article· en· W1488618428 on OpenAlexaffvenue
Rajiv Samant, T. J. Tucker

Bibliographic record

VenueCurrent Oncology · 2006
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsOttawa HospitalOttawa Regional Cancer FoundationUniversity of Ottawa
Fundersnot available
KeywordsMedicineRadiation therapyPalliative careNumber needed to treatIntensive care medicineAlternative medicineNursingSurgeryPathology

Abstract

fetched live from OpenAlex

The value of radiotherapy for palliation is well known to oncologists but not necessarily to other physicians. Using terms such as symptom improvement ratio (sir) and number needed to treat (nnt) rather than traditional response rates might be more appropriate in describing the benefits of palliative radiotherapy to other health care professionals.

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.

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)0.016
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.002
Science and technology studies0.0010.006
Scholarly communication0.0060.020
Open science0.0030.002
Research integrity0.0090.014
Insufficient payload (model declined to judge)0.0040.003

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 head0.400
Teacher spread0.220 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2006
Admission routes2
Has abstractyes

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