MétaCan
Menu
Back to cohort

Recovery of Locomotion After Spinal Cord Injury: Some Facts and Mechanisms

2011· review· en· W2164994619 on OpenAlexafffund
Serge Rossignol, Alain Frigon

Bibliographic record

VenueAnnual Review of Neuroscience · 2011
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité de SherbrookeUniversité de MontréalCanadian Institutes of Health Research
FundersCanadian Institutes of Health ResearchFordham University
KeywordsCentral pattern generatorNeuroscienceSpinal cordSpinal cord injurySensory systemHindlimbReflexPsychologyBiologyMedicineAnatomyRhythm

Abstract

fetched live from OpenAlex

After spinal cord injury (SCI), various sensorimotor functions can recover, ranging from simple spinal reflexes to more elaborate motor patterns, such as locomotion. Locomotor recovery after complete spinalization (complete SCI) must depend on the presence of spinal circuitry capable of generating the complex sequential activation of various leg muscles. This is achieved by an intrinsic spinal circuitry, termed the central pattern generator (CPG), working in conjunction with sensory feedback from the legs. After SCI, different changes in cellular and circuit properties occur spontaneously and can be promoted by pharmacological, electrical, or rehabilitation strategies. After partial SCI, hindlimb locomotor recovery can result from regeneration or sprouting of spared pathways, but also from mechanisms observed after complete SCI, namely changes within the intrinsic spinal circuitry and sensory inputs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.113
GPT teacher head0.442
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations326
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueAnnual Review of NeuroscienceSame topicSpinal Cord Injury ResearchFrench-language works237,207