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Record W2122329254 · doi:10.1126/scisignal.2005560

A Unified Nomenclature and Amino Acid Numbering for Human PTEN

2014· article· en· W2122329254 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Signaling · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsPrincess Margaret Cancer CentreQueen's University
FundersNational Institute of General Medical SciencesNational Cancer Institute
KeywordsPTENNumberingNomenclatureAmino acidComputational biologyBiologyCancer researchComputer scienceCell biologyBiochemistryProgramming languagePI3K/AKT/mTOR pathwaySignal transductionTaxonomy (biology)Botany

Abstract

fetched live from OpenAlex

The tumor suppressor PTEN is a major brake for cell transformation, mainly due to its phosphatidylinositol 3,4,5-trisphosphate [PI(3,4,5)P3] phosphatase activity that directly counteracts the oncogenicity of phosphoinositide 3-kinase (PI3K). PTEN mutations are frequent in tumors and in the germ line of patients with tumor predisposition or with neurological or cognitive disorders, which makes the PTEN gene and protein a major focus of interest in current biomedical research. After almost two decades of intense investigation on the 403-residue-long PTEN protein, a previously uncharacterized form of PTEN has been discovered that contains 173 amino-terminal extra amino acids, as a result of an alternate translation initiation site. To facilitate research in the field and to avoid ambiguities in the naming and identification of PTEN amino acids from publications and databases, we propose here a unifying nomenclature and amino acid numbering for this longer form of PTEN.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.283
Teacher spread0.270 · 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