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Record W2411387225 · doi:10.1227/neu.0000000000000950

The Burden of Spinal Disorders in the Elderly

2015· review· en· W2411387225 on OpenAlexaff
Robert Waldrop, Joseph Cheng, Clinton J. Devin, Matthew J. McGirt, Michael G. Fehlings, Sigurd Berven

Bibliographic record

VenueNeurosurgery · 2015
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDisease burdenHealth careBurden of diseaseQuality of life (healthcare)PopulationDiseaseEnvironmental healthPhysical therapyPathologyNursing

Abstract

fetched live from OpenAlex

Disorders of the spine are common and have a significant and measurable burden on affected patients and on our healthcare economy. The burden of spinal disorders encompasses metrics such as the prevalence of spinal disorders, the impact of spinal disorders on health-related quality of life, and the use of resources associated with the operative and nonoperative management of spinal disorders. Measurement of the burden of spinal disorders is important in prioritizing the distribution of limited resources within our healthcare economy. In 1998, the Priority Setting Committee of the Institute of Medicine concluded that in defining health priorities for research and funding, the burden of disease and impact on the health of the population should be the primary determinants of resource allocation. The purpose of this article is to report metrics comprising the burden of spinal disorders, with a focus on the significant and growing burden of spinal disorders in our elderly population, and to demonstrate that allocation of resources to the management of spinal disorders should be a priority for our healthcare economy.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.349
Teacher spread0.309 · 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

Citations92
Published2015
Admission routes1
Has abstractyes

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