MétaCan
Menu
Back to cohort
Record W2162845412 · doi:10.1517/14728222.11.10.1339

c-Jun N-terminal kinases as potential therapeutic targets

2007· review· en· W2162845412 on OpenAlexaff
Baljinder Salh

Bibliographic record

VenueExpert Opinion on Therapeutic Targets · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsUniversity of British Columbia
FundersUniversity of Otago
KeywordsKinaseDiseaseSignal transductionInflammationPathogenesisp38 mitogen-activated protein kinasesDiabetes mellitusc-junCancerBioinformaticsMedicineImmunologyBiologyCancer researchNeuroscienceCell biologyGeneProtein kinase AGeneticsTranscription factorPathologyEndocrinology

Abstract

fetched live from OpenAlex

One principal aim of research in the signal transduction field is to identify targets for therapeutic intervention, in an attempt to modify disease and curtail human suffering. Diseases such as chronic inflammation, atherosclerosis, diabetes and cancer exact a huge toll on health, in physical, social and financial terms. Defective signaling mechanisms are central to their pathogenesis. One candidate signaling molecule that is presently undergoing intense investigation is the c-Jun N-terminal kinase. With roles described in almost all classes of disease, the main questions are what type of inhibitor to use and when exactly to use it during the disease course?

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.057
GPT teacher head0.366
Teacher spread0.308 · 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 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

Citations38
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueExpert Opinion on Therapeutic TargetsSame topicMelanoma and MAPK PathwaysFrench-language works237,207