MétaCan
Menu
Back to cohort
Record W2322339970 · doi:10.2340/16501977-0974

Meeting the challenges of spinal cord injury care following sudden onset disaster: lessons learned

2012· article· en· W2322339970 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2012
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
FundersPan American Health Organization
KeywordsSpinal cord injuryMedicineHealth careSpinal cordMedical emergencyProcurementOccupational safety and healthPhysical medicine and rehabilitationBusinessPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Improved disaster response has led to higher survival rates and an increasing number of injuries in relation to deaths (injury to death ratio). Recent earthquakes, in particular, have led to unprecedented numbers of spinal cord injuries. Meeting the needs of individuals with spinal cord injuries is particularly challenging when disaster strikes a low resource environment. Clinicians who care for spinal cord injuries can learn from prior experiences and proactively address how to best meet needs in future disasters. Here we review and propose measures targeted to specific challenges including: coordination and mobilization; identification and procurement of required expertise; initial survey and assessment; health care delivery; community reintegration and health maintenance; and sustainability and capacity building.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.119
GPT teacher head0.491
Teacher spread0.372 · 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