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Record W2599361271 · doi:10.1080/15384101.2017.1302632

Tyr(less) kinase signaling during mitosis

2017· article· en· W2599361271 on OpenAlexaff
Sabine Elowe

Bibliographic record

VenueCell Cycle · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBiologyProtein tyrosine phosphataseCell biologyMitosisTyrosine phosphorylationPhosphoproteomicsPhosphorylationReceptor tyrosine kinaseTyrosineMitotic exitTyrosine kinaseSignal transductionProtein phosphorylationCell divisionSpindle apparatusCellBiochemistryProtein kinase A

Abstract

fetched live from OpenAlex

Tyrosine phosphorylation is rare, representing only about 0.5% of phosphorylations in the cell under basal conditions. While mitogenic tyrosine kinase signaling has been extensively explored, the role of phosphotyrosine signaling across the cell cycle and in particular during mitosis is poorly understood.Two recent, independent studies tackled this question from different angles to reveal exciting new insights into the role of this modification during cell division. Caron et al.Citation1 exploited mitotic phosphoproteomics data sets to determine the extent of mitotic tyrosine phosphorylation, and St-Denis et al.Citation2 identified protein tyrosine phosphatases from all subfamilies as regulators of mitotic progression or spindle formation. These studied collectively revealed that tyrosine phosphorylation may play a more prominent and active role in mitotic progression than previously appreciated.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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