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The Rb pathway in neurogenesis

2001· review· en· W2090046686 on OpenAlexaff
Kerry L. Ferguson, Ruth S. Slack

Bibliographic record

VenueNeuroreport · 2001
Typereview
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNeurogenesisCell fate determinationMitosisBiologyNeural developmentCell biologyCell cycleNeural stem cellCellular differentiationCell growthCell divisionRegulatorRetinoblastoma proteinRetinoblastomaNeurosciencePrecursor cellCellStem cellGeneticsTranscription factor

Abstract

fetched live from OpenAlex

Cell division during embryogenesis plays a crucial role in the formation of the nervous system. During this developmental process, proliferating neural precursor cells commit to a neuronal fate and, as a consequence, undergo terminal mitosis and adopt a neuronal phenotype. A key cell cycle regulator, the tumor suppressor protein, retinoblastoma (Rb), is involved in both terminal mitosis and neuronal differentiation. Neural development is a complex process involving cell proliferation, cell fate determination and differentiation, as well as programmed cell death. In this review, we will examine each of these processes in turn, focussing on the role of the Rb family proteins to examine their many influences on these events.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.060
GPT teacher head0.336
Teacher spread0.276 · 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

Citations58
Published2001
Admission routes1
Has abstractyes

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