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Record W2907784134 · doi:10.21037/apm.2018.12.04

Palliation of bone metastases—exploring options beyond radiotherapy

2019· review· en· W2907784134 on OpenAlexaff
Samantha Saravana-Bawan, Elizabeth David, Arjun Sahgal, Edward Chow

Bibliographic record

VenueAnnals of Palliative Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsSunnybrook Hospital
Fundersnot available
KeywordsMedicineRadiation therapyPalliative careGeneral surgeryIntensive care medicineRadiologyNursing

Abstract

fetched live from OpenAlex

Multiple new options are available in the palliation of bone metastases. Most of these techniques can be used in conjunction with radiation therapy either before or after and are now giving patients who have reached dose limitations new options. These techniques can also be used with vertebroplasty (VP) to increase structural stability post tumor ablation. Localized percutaneous treatment in the bone such as thermal [radiofrequency ablation (RFA)] and light [photodynamic therapy (PDT)] have been used to destroy tumor prior to injection with cement. This educational review will discuss the safety profile, technique and indications for emerging technology in the area of locoregional treatment of bone metastases in conjunction with vertebral augmentation. It will not delve comprehensively into conventional lines of treatment where indications and outcomes have already been well established.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.414
GPT teacher head0.477
Teacher spread0.063 · 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 designNot applicable
Domainnot available
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

Citations31
Published2019
Admission routes1
Has abstractyes

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