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Record W2976554815 · doi:10.1080/10790268.2019.1661697

Recommendations for evaluation of bladder and bowel function in pre-clinical spinal cord injury research

2019· review· en· W2976554815 on OpenAlexaff
Gregory M. Holmes, Charles H. Hubscher, Andrei V. Krassioukov, Lyn B. Jakeman, Naomi Kleitman

Bibliographic record

VenueJournal of Spinal Cord Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsInternational Collaboration On Repair DiscoveriesGF Strong Rehabilitation CentreUniversity of British Columbia
Fundersnot available
KeywordsSpinal cord injuryMedicinePhysical therapyUrinary bladderPhysical medicine and rehabilitationUrologySpinal cord

Abstract

fetched live from OpenAlex

Several fundamental assessments share reasonable levels of technical and material investment, including some that could assess bladder and bowel function non-invasively and simultaneously. Such measures used more inclusively across SCI studies would advance progress in this high priority area. When complemented with a few additional investigator-selected study-relevant supplemental measures, they are highly recommended for research programs investigating the efficacy of therapeutic interventions in preclinical animal models of SCI that have a bladder and/or bowel focus.

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)0.035
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.615
GPT teacher head0.649
Teacher spread0.035 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations17
Published2019
Admission routes1
Has abstractyes

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