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Record W2944528098 · doi:10.1126/sciadv.aau8857

Autophagy induction in atrophic muscle cells requires ULK1 activation by TRIM32 through unanchored K63-linked polyubiquitin chains

2019· article· en· W2944528098 on OpenAlexaff
Martina Di Rienzo, Manuela Antonioli, Carmela Fusco, Yuangang Liu, Muriel Mari, Idil Orhon, Giulia Refolo, F. Germani, Marco Corazzari, Alessandra Romagnoli, Fabiola Ciccosanti, Barbara Mandriani, Maria Teresa Pellico, Rachel De La Torre, Hao Ding, Monica Dentice, Marcella Neri, Alessandra Ferlini, Fulvio Reggiori, Molly Kulesz‐Martin, Mauro Piacentini, Giuseppe Merla, Gian María Fimia

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesH2020 Marie Skłodowska-Curie ActionsRegione LazioNederlandse Organisatie voor Wetenschappelijk OnderzoekFondazione TelethonAssociazione Italiana per la Ricerca sul CancroZonMw
KeywordsAutophagyULK1Muscular dystrophyMuscle atrophyAtrophyCell biologyMutationMedicineBiologyChemistryGeneticsKinaseGeneProtein kinase A

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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 score0.006

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.302
Teacher spread0.288 · 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

Citations112
Published2019
Admission routes1
Has abstractyes

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