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Record W1992368455 · doi:10.1310/sci1404-1

Detection and Treatment of Sublesional Osteoporosis Among Patients with Chronic Spinal Cord Injury

2009· article· en· W1992368455 on OpenAlexaff
B. Catharine Craven, Robertson, McGillivray, Adachi

Bibliographic record

VenueTopics in Spinal Cord Injury Rehabilitation · 2009
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsSt. Joseph’s Healthcare HamiltonHamilton Health SciencesHamilton General HospitalToronto Rehabilitation Institute
Fundersnot available
KeywordsMedicineOsteoporosisSpinal cord injuryRehabilitationBone mineralPhysical therapyBisphosphonateSpinal cordInternal medicine

Abstract

fetched live from OpenAlex

Low hip and knee region bone mineral density (BMD) after spinal cord injury (SCI) results in an increased risk of lower extremity fragility fractures or sublesional osteoporosis (SLOP). There are currently no guidelines for the identification and treatment of SLOP among patients with chronic SCI. A paradigm for identification (medical screening, fracture risk, and bone mineral density assessment) of persons with SLOP who warrant treatment and selection of appropriate SLOP treatment(s) (lifestyle/nutrition modifications, bisphosphonate/rehabilitation therapies) is proposed. Content is based on the authors’ opinions/expertise and available published and unpublished literature and is intended for use by rehabilitation professionals.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.307
Teacher spread0.291 · 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 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

Citations55
Published2009
Admission routes1
Has abstractyes

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