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Record W317138968 · doi:10.1017/cbo9780511541759

Neurobiology of Peripheral Nerve Regeneration

2008· book· en· W317138968 on OpenAlexaff
Douglas W. Zochodne

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNeuroscienceRegeneration (biology)Peripheral nervePeripheral nervous systemPeripheralMedicinePsychologyCentral nervous systemBiologyAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Peripheral nerve disorders are among the most common neurological problems that clinicians face, yet few therapies and interventions are available to arrest or reverse the damage associated with them. Summarising this important, but neglected, area of neuroscience, Doug Zochodne addresses the peripheral nervous system and its unique neurobiology. He summarises current basic ideas about the molecular mechanisms involved in both nerve degeneration and regeneration and what approaches can be used to address it experimentally. Heavily illustrated throughout, and including a 32 page colour plate section, this book will serve as a valuable reference for academic researchers and graduate students.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.010

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 head0.033
GPT teacher head0.215
Teacher spread0.183 · 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
GenreOther

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

Citations120
Published2008
Admission routes1
Has abstractyes

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