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Record W2443613404 · doi:10.1016/j.ccell.2016.05.002

Inhibition of Dopamine Receptor D4 Impedes Autophagic Flux, Proliferation, and Survival of Glioblastoma Stem Cells

2016· article· en· W2443613404 on OpenAlexafffund
Sonam Dolma, Hayden Selvadurai, Xiaoyang Lan, Lilian Lee, Michelle Kushida, Véronique Voisin, Heather Whetstone, Milly So, Tzvi Aviv, Nicole Park, Xueming Zhu, Changjiang Xu, Renee Head, Katherine Rowland, Mark Bernstein, Ian D. Clarke, Gary D. Bader, Lea Harrington, John H. Brumell, Mike Tyers, Peter B. Dirks

Bibliographic record

VenueCancer Cell · 2016
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and CancerHospital for Sick ChildrenOntario College of Art and DesignToronto Western HospitalSickKids FoundationUniversity of Toronto
FundersNational Institute of General Medical SciencesGenome CanadaCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchEuropean Research CouncilNational Institutes of HealthOntario Institute for Cancer Research
KeywordsAutophagyNeurochemicalNeural stem cellCell biologyStem cellPI3K/AKT/mTOR pathwayBiologyDopamineCell growthDopaminergicVacuoleNeuroscienceCancer researchSignal transductionChemistryApoptosisCytoplasmBiochemistry

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

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)0.000
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 score0.012
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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 teacher head, 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

Citations216
Published2016
Admission routes2
Has abstractno

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