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The p53 family in nervous system development and disease

2006· review· en· W2090734379 on OpenAlexaff
W. Bradley Jacobs, David R. Kaplan, Freda D. Miller

Bibliographic record

VenueJournal of Neurochemistry · 2006
Typereview
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsInstitute of Cancer ResearchHospital for Sick Children
Fundersnot available
KeywordsApoptosisNervous systemSuppressorNeuroscienceFunction (biology)BiologyDiseaseCentral nervous systemSympathetic nervous systemCell biologyMedicineCancerInternal medicineEndocrinologyGenetics

Abstract

fetched live from OpenAlex

The p53 family, consisting of the tumor suppressors p53, p63 and p73, play a vital role as regulators of survival and apoptosis in the developing, adult and injured nervous system. These proteins function as key survival and apoptosis checkpoints in neurons, acting as either rheostats or sensors responsible for integrating multiple pro-apoptotic and survival cues. A dramatic example of this checkpoint function is observed in developing sympathetic neurons, where a pro-survival and truncated form of p73 antagonizes the apoptotic functions of p53 and p63. Thus the levels and activities of the different p53 family members may ultimately determine whether neurons either live or die during nervous system development and disease.

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 score0.004
Threshold uncertainty score0.014

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 studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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

Citations114
Published2006
Admission routes1
Has abstractyes

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