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Record W2947504297 · doi:10.1002/dvdy.64

The generation of granule cells during the development and evolution of the cerebellum

2019· review· en· W2947504297 on OpenAlexafffund
Angelo Iulianella, Richard Wingate, Cecilia B. Moens, Emily Capaldo

Bibliographic record

VenueDevelopmental Dynamics · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsHindbrainCerebellumGranule cellBiologyNeuroscienceCerebellar cortexVestibular systemAnatomyDorsumCell typeSensory systemGranule (geology)CellCentral nervous systemGeneticsDentate gyrus

Abstract

fetched live from OpenAlex

The cerebellum coordinates vestibular input into the hindbrain to control balance and movement, and its anatomical complexity is increasingly viewed as a high-throughput processing center for sensory and cognitive functions. Cerebellum development however is relatively simple, and arises from a specialized structure in the anterior hindbrain called the rhombic lip, which along with the ventricular zone of the rostral-most dorsal hindbrain region, give rise to the distinct cell types that constitute the cerebellum. Granule cells, being the most numerous cell types, arise from the rhombic lip and form a dense and distinct layer of the cerebellar cortex. In this short review, we describe the various strategies used by amniotes and anamniotes to generate and diversify granule cell types during cerebellar development.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.051
GPT teacher head0.250
Teacher spread0.199 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

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