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Surgical Treatment for the Painful Motion Segment

2005· review· en· W2063894596 on OpenAlexaff
David W. Polly, Edward Santos, Amir A. Mehbod

Bibliographic record

VenueSpine · 2005
Typereview
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicineSurgery

Abstract

fetched live from OpenAlex

STUDY DESIGN: A convenience literature-based review of the different techniques of posterior lumbar fusion. OBJECTIVE: To describe the history, specific techniques, and outcomes of different methods of posterior lumbar fusion. The specific methods that were described include 1) uninstrumented posterior, posterolateral, and facet fusion, and 2) instrumented fusion using pedicle screws or facet screws. SUMMARY OF BACKGROUND DATA: There are various posterior fusion techniques available for the treatment of degenerative lumbar spine conditions. Each individual technique has specific technical demands, indications, advantages, and disadvantages which should be taken into consideration when performing these procedures. METHODS: The published scientific literature on the different methods of posterior lumbar fusion was reviewed. The history, indications, advantages, disadvantages, and clinical and radiographic outcomes were described based on the literature search. RESULTS/CONCLUSIONS: Posterior fusion techniques have been and will continue to be among the most commonly performed procedures in lumbar spine surgery. The different methods of fusion are well defined, as are the possible complications and outcomes. They are effective techniques when performed on appropriately selected patients by a surgeon knowledgeable in the techniques and indications. Further studies are needed regarding promising but relatively unproven developments such as minimally invasive surgery and the use of osteoinductive agents.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.994
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.127
GPT teacher head0.424
Teacher spread0.298 · 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 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

Citations89
Published2005
Admission routes1
Has abstractyes

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