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Record W2811499691 · doi:10.1038/s41386-018-0136-3

The effects of ketamine on prefrontal glutamate neurotransmission in healthy and depressed subjects

2018· article· en· W2811499691 on OpenAlexfundno aff
Chadi G. Abdallah, Henk M. De Feyter, Lynnette A. Averill, Lihong Jiang, Christopher L. Averill, Golam M. I. Chowdhury, Prerana Purohit, Robin A. de Graaf, Irina Esterlis, Christoph Juchem, Brian Pittman, John H. Krystal, Douglas L. Rothman, Gerard Sanacora, Graeme F. Mason

Bibliographic record

VenueNeuropsychopharmacology · 2018
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of Mental HealthNational Institute on AgingNational Institute on Alcohol Abuse and AlcoholismNational Center for PTSD, U.S. Department of Veterans AffairsNovartis PharmaAstellas Pharma Global DevelopmentGenentechGeorgia Clinical and Translational Science AllianceAstellas PharmaOtsuka AmericaFORUM PharmaceuticalsVistagen TherapeuticsUCB PharmaValeant Pharmaceuticals InternationalH. Lundbeck A/SSunovionSanofiNational Alliance for Research on Schizophrenia and DepressionAmerican Psychiatric FoundationBristol-Myers SquibbEli Lilly and CompanyAllerganAstraZenecaPfizerOtsuka America PharmaceuticalAmgenNational Institutes of HealthYale Center for Clinical Investigation, Yale School of MedicineJanssen PharmaceuticalsSage TherapeuticsU.S. Department of Health and Human ServicesTeva Pharmaceutical IndustriesU.S. Department of Veterans AffairsYale University
KeywordsPsychologyNeurotransmissionGlutamate receptorKetamineNeurosciencePrefrontal cortexMedicineInternal medicineCognitionReceptor

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 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.309
Teacher spread0.300 · 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 designObservational
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

Citations226
Published2018
Admission routes1
Has abstractno

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