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Record W2958412423 · doi:10.1016/j.gde.2019.06.004

Integrating chemical and mechanical signals in neural crest cell migration

2019· review· en· W2958412423 on OpenAlexfundno aff
Adam Shellard, Roberto Mayor

Bibliographic record

VenueCurrent Opinion in Genetics & Development · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilMedical Research Council CanadaWellcome Trust
KeywordsNeural crestBiologyCranial neural crestSkullCell migrationPopulationAnatomyNeuroscienceEmbryonic stem cellCrestCellCell biologyEmbryoGenetics

Abstract

fetched live from OpenAlex

Neural crest cells are a multipotent embryonic stem cell population that migrate large distances to contribute a variety of tissues. The cranial neural crest, which contribute to tissues of the face and skull, undergo collective migration whose movement has been likened to cancer metastasis. Over the last few years, a variety of mechanisms for the guidance of collective cranial neural crest cell migration have been described: mostly chemical, but more recently mechanical. Here we review these different mechanisms and attempt to integrate them to provide a unified model of collective cranial neural crest cell migration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.354
Teacher spread0.293 · 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 teacher head, not a consensus.

Study designOther design
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

Citations72
Published2019
Admission routes1
Has abstractyes

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