MétaCan
Menu
Back to cohort

The Elegance of Sonic Hedgehog: Emerging Novel Functions for a Classic Morphogen

2018· review· en· W2898626672 on OpenAlexafffund
A. Denise R. Garcia, Young-Goo Han, Jason W. Triplett, W. Todd Farmer, Corey C. Harwell, Rebecca A. Ihrie

Bibliographic record

VenueJournal of Neuroscience · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal General HospitalMontreal Neurological Institute and Hospital
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Cancer InstituteNational Institutes of HealthFondation Brain CanadaW. Garfield Weston FoundationMcGill UniversityMcGill University Health CentreNational Eye InstituteVanderbilt UniversityEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. Department of Defense
KeywordsMorphogenSonic hedgehogNeuroscienceBiologyHedgehogMorphogenesisEmbryonic stem cellHedgehog signaling pathwaySignallingFunction (biology)Signal transductionCell biologyGenetics

Abstract

fetched live from OpenAlex

Sonic Hedgehog (SHH) signaling has been most widely known for its role in specifying region and cell-type identity during embryonic morphogenesis. This mini-review accompanies a 2018 SFN mini-symposium that addresses an emerging body of research focused on understanding the diverse roles for Shh signaling in a wide range of contexts in neurodevelopment and, more recently, in the mature CNS. Such research shows that Shh affects the function of brain circuits, including the production and maintenance of diverse cell types and the establishment of wiring specificity. Here, we review these novel and unexpected functions and the unanswered questions regarding the role of SHH and its signaling pathway members in these cases.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.094
GPT teacher head0.359
Teacher spread0.265 · 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

Citations57
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicHedgehog Signaling Pathway StudiesFrench-language works237,207