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Record W2007823025 · doi:10.3171/spi.2005.2.1.0040

Use of “MAPS” for determining the optimal surgical approach to metastatic disease of the thoracolumbar spine: anterior, posterior, or combined

2005· article· en· W2007823025 on OpenAlexaff
Daryl R. Fourney, Ziya L. Gokaslan

Bibliographic record

VenueJournal of Neurosurgery Spine · 2005
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMedicineSurgeryMnemonicSpinal diseaseSpinal surgerySurgical proceduresResectionDiseaseSurgical planningRachisLumbarPathology

Abstract

fetched live from OpenAlex

The surgical treatment of thoracolumbar metastases is controversial, and various approaches have been described. No single approach, however, is always applicable, and the optimal surgical strategy for any individual is determined by several interrelated factors. The authors have grouped these factors into four preoperative planning considerations that form the mnemonic "MAPS": 1) method of resection; 2) anatomy of spinal disease; 3) patient's level of fitness; and 4) stabilization. The choice of approach is also considered in light of the goals of surgery, including the relief of pain, neurological palliation, spinal stabilization, and oncological control.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.069
GPT teacher head0.321
Teacher spread0.252 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations23
Published2005
Admission routes1
Has abstractyes

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