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Record W2065504839 · doi:10.1016/j.cellsig.2012.08.008

Nerve growth factor stimulation of ERK1/2 phosphorylation requires both p75NTR and α9β1 integrin and confers myoprotection towards ischemia in C2C12 skeletal muscle cell model

2012· article· en· W2065504839 on OpenAlexaff
Keren Ettinger, Shimon Lecht, Hadar Arien‐Zakay, Gadi Cohen, Shlomit Aga‐Mizrachi, Nurit Yanay, H. Uri Saragovi, Hinyu Nedev, Cezary Marcinkiewicz, Yoram Nevo, Philip Lazarovici

Bibliographic record

VenueCellular Signalling · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsMcGill UniversityJewish General Hospital
FundersDavid R. Bloom Center for Pharmacy, Hebrew University of JerusalemNational Institutes of HealthHebrew University of JerusalemNational Cancer InstituteAmerican Society for Pharmacology and Experimental Therapeutics
KeywordsMyogenesisNerve growth factorC2C12MyocytePhosphorylationSkeletal muscleCell biologyTropomyosin receptor kinase AInternal medicineChemistryEndocrinologyAutocrine signallingMAPK/ERK pathwaySignal transductionBiologyReceptorBiochemistryMedicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.249
Teacher spread0.214 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations23
Published2012
Admission routes1
Has abstractno

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