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Record W4247132859 · doi:10.1002/rnj.27

Therapeutic Horse Back Riding of a Spinal Cord Injured Veteran: A Case Study

2012· article· en· W4247132859 on OpenAlexfundno aff
Glennys Asselin, Julius H. Penning, Savithri Ramanujam, Rebecca Colina Neri, Constance Ward

Bibliographic record

VenueRehabilitation Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsnot available
FundersReseau canadien de recherche respiratoire
KeywordsMedicineHorsePhysical medicine and rehabilitationSpinal cordSpinal cord injuryPhysical therapy

Abstract

fetched live from OpenAlex

Purpose To determine an incomplete spinal cord injured veteran's experience following participation in a therapeutic horseback riding program. Methods Following the establishment of a nationwide therapeutic riding program for America's wounded service veterans in 2007, a Certified Rehabilitation Registered Nurse from the Michael E. DeBakey Veteran Affairs Medical Center worked with an incomplete spinal cord injured veteran who participated in the Horses for Heroes program. Results This program resulted in many benefits for the veteran, including an increase in balance, muscle strength, and self-esteem. Discussion A physical, psychological, and psychosocial benefit of therapeutic horseback riding is shown to have positive results for the spinal cord injured. Therapeutic riding is an emerging field where the horse is used as a tool for physical therapy, emotional growth, and learning. Conclusion Veterans returning from the Iraq/Afghanistan war with traumatic brain injuries, blast injuries, depression, traumatic amputations, and spinal cord injuries may benefit from this nurse-assisted therapy involving the horse.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.104
GPT teacher head0.472
Teacher spread0.368 · 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 teacher head, 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

Citations2
Published2012
Admission routes1
Has abstractyes

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