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The Servitization of the Aerospace Industry and the effects on product development

2013· article· en· W34697074 on OpenAlexfundno aff
Johanna Wallin

Bibliographic record

VenueeNeuro · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsnot available
FundersVINNOVAUniversity of Saskatchewan
KeywordsAerospaceProduct (mathematics)Service (business)New product developmentBusinessProduct-service systemProcess managementEngineeringManufacturing engineeringMarketingBusiness model

Abstract

fetched live from OpenAlex

Heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) is an RNA binding protein (RBP) that is localized within neurons and plays crucial roles in RNA metabolism. Its importance in neuronal functioning is underscored from the study of its pathogenic features in many neurodegenerative diseases where neuronal hnRNP A1 is mislocalized from the nucleus to the cytoplasm resulting in loss of hnRNP A1 function. Here, we model hnRNP A1 loss-of-function by siRNA-mediated knock-down in differentiated Neuro-2a cells. Through RNA sequencing (RNA-seq) followed by gene ontology (GO) analyses, we show that hnRNP A1 is involved in important biological processes, including RNA metabolism, neuronal function, neuronal morphology, neuronal viability, and stress granule (SG) formation. We further confirmed several of these roles by showing that hnRNP A1 knock-down results in a reduction of neurite outgrowth, increase in cell cytotoxicity and changes in SG formation. In summary, these findings indicate that hnRNP A1 loss-of-function contributes to neuronal dysfunction and cell death and implicates hnRNP A1 dysfunction in the pathogenesis of neurodegenerative diseases.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.179
Teacher spread0.172 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2013
Admission routes1
Has abstractyes

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