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Record W2963063733 · doi:10.1259/bjr.20190211

Spinal metastasis: diagnosis, management and follow-up

2019· review· en· W2963063733 on OpenAlexaff
Mahmud Mossa‐Basha, Peter C. Gerszten, Sten Myrehaug, Nina A. Mayr, William T. C. Yuh, Pejman Maralani, Arjun Sahgal, Simon S. Lo

Bibliographic record

VenueBritish Journal of Radiology · 2019
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineMultidisciplinary approachRadiation therapyDiseaseRadiation treatment planningMagnetic resonance imagingSpinal cordMetastasisSpinal columnRadiologyIntensive care medicineCancerMedical physicsSurgeryPathologyInternal medicine

Abstract

fetched live from OpenAlex

Spine metastatic disease is an increasingly common occurrence in cancer patients due to improved patient survival. Close proximity of the bony spinal column to the spinal cord limits many conventional treatments for metastatic disease. In the past decade, we have witnessed dramatic advancements in therapies, with improvements in surgical techniques and recent adoption of spine stereotactic radiotherapy techniques leading to improved patient outcomes. Multidisciplinary approaches to patient evaluation, treatment and follow-up are essential. Imaging plays an ever increasing role in disease detection, pre-treatment planning and assessment of patient outcomes. It is important for the radiologist to be familiar with imaging algorithms, best practices for surgery and/or radiotherapy and imaging findings in the post-treatment period that may indicate disease recurrence. In this review, we present a multidisciplinary discussion of spine metastases, with specific focus on pre-treatment imaging, planning, current treatment approaches, and post-treatment assessment.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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 head0.061
GPT teacher head0.346
Teacher spread0.285 · 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 teacher head, not a consensus.

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

Citations63
Published2019
Admission routes1
Has abstractyes

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