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Record W2563751073 · doi:10.1089/neu.2016.4751

2015 ParaPan American Games: Autonomic Function, But Not Physical Activity, Is Associated with Vascular-Cognitive Impairment in Spinal Cord Injury

2016· article· en· W2563751073 on OpenAlexafffund
Aaron A. Phillips, Jordan W. Squair, Katharine D. Currie, Yu‐Chieh Tzeng, Philip N. Ainslie, Andrei V. Krassioukov

Bibliographic record

VenueJournal of Neurotrauma · 2016
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of British ColumbiaInternational Collaboration On Repair Discoveries
FundersCanadian Institutes of Health Research
KeywordsSpinal cord injuryMedicinePhysical medicine and rehabilitationCerebral blood flowStroop effectPhysical therapyCognitionPsychologyCardiologySpinal cord

Abstract

fetched live from OpenAlex

Autonomic dysfunction and diminished capacity for physical exercise are commonly implicated in the 3- to 4-fold increased risk of cerebrovascular disease after spinal cord injury (SCI). We assessed cerebrovascular function (transcranial Doppler; neurovascular coupling [NVC], and cerebral pressure-flow regulation) in elite national level wheelchair rugby players (n = 23), normally active SCI individuals (n = 12), and able-bodied controls (n = 13). Cognitive (Stroop test) and autonomic function (postural change) also were evaluated. SCI individuals demonstrated reduced posterior cerebral blood flow, as well as impaired cerebrovascular and cognitive function. Autonomic dysfunction but not physical activity was related to impaired NVC and cerebral pressure-flow regulation after SCI. Routine upper-body exercise, as utilized by elite wheelchair rugby athletes, may not elicit beneficial cerebrovascular effects. On the other hand, autonomic dysfunction needs to be considered a key culprit in cerebrovascular diseases after SCI.

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 score0.817
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.398
Teacher spread0.324 · 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

Citations31
Published2016
Admission routes2
Has abstractyes

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