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The Molecular Basis of Neural Regeneration

2003· review· en· W2056850367 on OpenAlexaff
W. Bradley Jacobs, Michael G. Fehlings

Bibliographic record

VenueNeurosurgery · 2003
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsRegeneration (biology)NeuroscienceCentral nervous systemMedicineInhibitory postsynaptic potentialFunction (biology)BiologyCell biology

Abstract

fetched live from OpenAlex

THE CENTRAL NERVOUS SYSTEM (CNS) is incapable of meaningful regeneration of lost neurons or axonal and dendritic connections after injury. This often results in permanent and severe loss of neurological function. The CNS regenerative process is unsuccessful for at least three reasons: neurons are highly susceptible to death after CNS injury; the CNS extracellular milieu contains multiple inhibitory factors that make it nonpermissive to growth; and the intrinsic growth capacity of postmitotic neurons is constitutively reduced. However, a number of recent developments in each of these areas is providing insight into the cellular mechanisms involved in CNS regeneration and may eventually lead to the development of therapies capable of effecting successful CNS regeneration.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.078
GPT teacher head0.323
Teacher spread0.245 · 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 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

Citations59
Published2003
Admission routes1
Has abstractyes

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