MétaCan
Menu
Back to cohort
Record W4393910131 · doi:10.1016/j.neo.2024.100994

Retraction notice to “Role of Autophagy as a Survival Mechanism for Hypoxic Cells in Tumors” [Neoplasia 18 (2016) 347- 355/201]

2024· article· en· W4393910131 on OpenAlexaff
Qian Tan, Marina Wang, Man Yu, Junyan Zhang, Robert G. Bristow, Rićhard P. Hill, Ian F. Tannock

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueNeoplasia · 2024
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsNoticeAutophagyMechanism (biology)Cancer researchHypoxia (environmental)MedicineBiologyPathologyCell biologyChemistryPhilosophyGeneticsPolitical scienceOxygenApoptosisLawEpistemology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaResearch integrity
Domain: not available · Genre: Editorial
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptMetaresearchResearch integrity
Domain: Methods · Genre: Editorial
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.986
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.029
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0040.002
Scholarly communication0.0050.003
Open science0.0040.003
Research integrity0.0140.017
Insufficient payload (model declined to judge)0.0370.025

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 head0.291
Teacher spread0.279 · 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

Labeled directly by 2 models reading the full record.

Research integrityMetaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable
DomainMethods
GenreEditorial

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

Citations0
Published2024
Admission routes1
Has abstractno

Explore more

Same venueNeoplasiaSame topicAutophagy in Disease and TherapyCategoryResearch integrityFrench-language works237,207