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Record W2499277835 · doi:10.1080/10790268.2016.1182696

Primary care for persons with spinal cord injury — not a novel idea but still under-developed

2016· article· en· W2499277835 on OpenAlexaff
Chester Ho

Bibliographic record

VenueJournal of Spinal Cord Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsPrimary careSpinal cord injuryNursingHealth careMedicinePrimary health carePsychologyFamily medicinePolitical sciencePsychiatrySpinal cord

Abstract

fetched live from OpenAlex

Primary care for persons with spinal cord injury (SCI) has long been recognized as an important issue. Over the last two decades, there has not been any consensus on its contents, pathway or delivery model. Despite the lack of attention on this issue, various health care organizations and settings have successfully developed their own version of primary care for persons with SCI. On the other hand, persons with SCI have also found different ways to obtain primary care through Family Physicians and specialists, often depending on the health care structure of their country. This has blurred the line between what is traditionally seen as primary vs. specialist care. The "medical home" model may be ideal for SCI primary care, and it may be establishsed in different care settings. In order to create this model, health care funding structure, appropriate access to physical facility and SCI knowledge, interdisciplinary provider availability and collaboration, as well as active engagement with persons with SCI are necessary. The SCI community should endorse SCI primary care with effective advocacy and implementation.

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)0.008
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.005
Scholarly communication0.0060.006
Open science0.0020.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.113
GPT teacher head0.412
Teacher spread0.299 · 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
GenreCommentary

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

Citations24
Published2016
Admission routes1
Has abstractyes

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