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Record W3097357285 · doi:10.46292/sci2603-209

A Primary Care Provider’s Guide to Preventive Health After Spinal Cord Injury

2020· article· en· W3097357285 on OpenAlexaff
James Milligan, Stephen P. Burns, Suzanne L. Groah, Jeremy Howcroft

Bibliographic record

VenueTopics in Spinal Cord Injury Rehabilitation · 2020
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsEmmanuel Bible CollegeCentre for Family Medicine
Fundersnot available
KeywordsMedicineSpinal cord injuryPreventive careHealth careHealth maintenancePrimary carePreventive healthcarePopulationNursingMedical emergencyFamily medicinePublic healthEnvironmental healthSpinal cordPsychiatry

Abstract

fetched live from OpenAlex

Abstract Objective: Provide guidance for preventive health and health maintenance after spinal cord injury (SCI) for primary care providers (PCPs). Main message: Individuals with SCI may not receive the same preventive health care as the general population. Additionally, SCI-related secondary conditions may put their health at risk. SCI is considered a complex condition associated with many barriers to receiving quality primary care. Attention to routine preventive care and the unique health considerations of persons with SCI can improve health and quality of life and may prevent unnecessary health care utilization. Conclusion: PCPs are experts in preventive care and continuity of care, however individuals with SCI may not receive the same preventive care due to numerous barriers. This article serves as a quick reference for PCPs.

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)0.002
metaresearch head score (Gemma)0.015
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0960.040

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 head0.042
GPT teacher head0.426
Teacher spread0.384 · 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
GenreOther

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

Citations8
Published2020
Admission routes1
Has abstractyes

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