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Record W2326828834 · doi:10.4161/auto.20828

Targeting autophagy

2012· article· hu· W2326828834 on OpenAlex
Sharon M. Gorski, Jenna Ries, Julian J. Lum

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAutophagy · 2012
Typearticle
Languagehu
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of VictoriaSimon Fraser UniversityBurnaby HospitalBC Cancer Agency
FundersCanadian Institutes of Health ResearchMerck CanadaTakeda OncologySimon Fraser UniversityUniversity of Glasgow
KeywordsAutophagyBiologyCancerBasic researchDrug developmentClinical trialDiseaseTranslational researchDrug discoveryMechanism (biology)Cancer researchBioinformaticsDrugPharmacologyBiotechnologyGeneticsMedicineInternal medicineLibrary scienceApoptosis

Abstract

fetched live from OpenAlex

In recent years, tremendous progress has been made toward unveiling the mechanism of autophagy and its exploitation by many different cancer types. This year the American Association for the Advancement of Science held a one day Symposium on Autophagy: An Emerging Therapeutic Target in Human Disease in Vancouver, British Columbia and brought together experts in cell biology, drug discovery, and clinical translation to share their research findings and prospects. Currently, autophagy is being investigated on several fronts, from modulation of gene expression to in vivo studies, and more recently clinical trials in cancer. Key topics of discussion were determining which stage of autophagy would be the ideal target for inhibition to produce the highest impact, and which cancers or cancer subtypes would be the most sensitive to autophagy inhibitors; the answers to these questions may be a turning point in cancer therapy research.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.013

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 head0.018
GPT teacher head0.295
Teacher spread0.277 · 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