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Record W2071783567 · doi:10.1002/jnr.1255

Spinal cord reconstruction using NeuroGel™ implants and functional recovery after chronic injury

2001· article· en· W2071783567 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 Neuroscience Research · 2001
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsWSP (Canada)
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthUniversity of Alabama at Birmingham
KeywordsSpinal cord injuryMedicineLesionSpinal cordCordSpinal cord compressionSurgery

Abstract

fetched live from OpenAlex

There is currently a lack of effective ways to achieve functional tissue repair of the chronically injured spinal cord. We investigated the potential of using NeuroGel, a biocompatible polymer hydrogel, to induce a reconstruction of the rat spinal cord after chronic compression-produced injury. NeuroGel was inserted 3 months after a severe injury into the post-traumatic lesion cavity. Rats were placed in an enriched environment and the functional deficits were measured using the BBB rating scale. A significant improvement in the mean BBB scores was observed. Rats without enriched environment and severely injured rats with an enriched environment alone showed no improvement; however, 7 months after reconstructive surgery using NeuroGel, a reparative neural tissue had formed within the polymer gel that included myelinated axons and dendro-dendritic contacts. NeuroGel implantation into a chronic spinal cord injury therefore resulted in tissue reconstruction and functional improvement, suggesting that such an approach may have therapeutic value in the repair of focal lesions in humans.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.798
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.217
GPT teacher head0.474
Teacher spread0.256 · 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