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Record W1936685714 · doi:10.1007/s12311-015-0724-2

Consensus Paper: Cerebellar Development

2015· review· en· W1936685714 on OpenAlexaff
Ketty Leto, Marife Arancillo, Esther B. E. Becker, Annalisa Buffo, Chin Chiang, Baojin Ding, William B. Dobyns, Isabelle Dusart, Parthiv Haldipur, Mary E. Hatten, Mikio Hoshino, Alexandra L. Joyner, Masanobu Kano, Daniel L. Kilpatrick, Noriyuki Koibuchi, Silvia Marino, Salvador Martı́nez, Kathleen J. Millen, Thomas O Millner, Takaki Miyata, Elena Parmigiani, Karl Schilling, Gabriella Sekerková, Roy V. Sillitoe, Constantino Sotelo, Naofumi Uesaka, Annika K. Wefers, Richard Wingate, Richard Hawkes

Bibliographic record

VenueThe Cerebellum · 2015
Typereview
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsUniversity of Calgary
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Neurological Disorders and StrokeParkinsonfondenUniversità degli Studi di TorinoNational Cancer InstituteNational Ataxia FoundationNational Institutes of HealthNational Institute of Mental HealthRoyal SocietyAtaxia UKTexas Children's HospitalIntellectual and Developmental Disabilities Research CenterBachmann-Strauss Dystonia and Parkinson Foundation
KeywordsCerebellumNeurosciencePurkinje cellProgenitor cellBiologyCerebellar diseasesStem cellCell biology

Abstract

fetched live from OpenAlex

The development of the mammalian cerebellum is orchestrated by both cell-autonomous programs and inductive environmental influences. Here, we describe the main processes of cerebellar ontogenesis, highlighting the neurogenic strategies used by developing progenitors, the genetic programs involved in cell fate specification, the progressive changes of structural organization, and some of the better-known abnormalities associated with developmental disorders of the cerebellum.

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)0.003
metaresearch head score (Gemma)0.007
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: Review · Consensus signal: Review
Teacher disagreement score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0400.033

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 head0.105
GPT teacher head0.337
Teacher spread0.232 · 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

Citations499
Published2015
Admission routes1
Has abstractyes

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