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Record W1971449112 · doi:10.1139/z00-198

Neuronal growth and target recognition: lessons from the leech

2001· article· en· W1971449112 on OpenAlexfundvenueno aff
Michael W. Baker, Eduardo R. Macagno

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthNational Science Foundation
KeywordsLeechBiologyNeuroscienceNervous systemFunction (biology)Central nervous systemNeuronAnatomyEvolutionary biology

Abstract

fetched live from OpenAlex

The nervous system of the leech has been the subject of numerous studies since its "rediscovery" in the 1960s as a unique system for the study of the properties of glial cells. Subsequently, anatomical, physiological, and embryological studies of identified neurons have yielded a wealth of information about the differentiation of neuronal structure and function. In recent years, cellular approaches to the development of identified central and peripheral neurons have been complemented by molecular studies that promise to reveal the mechanisms by which neurons form their complex arbors and innervate specific targets.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.063
GPT teacher head0.260
Teacher spread0.197 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of ZoologySame topicAxon Guidance and Neuronal SignalingFrench-language works237,207