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Record W6887883925 · doi:10.17632/pj9tkpn7vm

Effects of Ketamine on Postoperative Cognition: A Scoping Review Dataset

2025· dataset· en· W6887883925 on OpenAlexaff

Bibliographic record

VenueMendeley Data · 2025
Typedataset
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKetamineCognitionRetrospective cohort studyClinical trialCohortPostoperative cognitive dysfunction

Abstract

fetched live from OpenAlex

This dataset was compiled to investigate the effects of ketamine on postoperative cognitive function in human study participants. It comprises data from 58 clinical trials and retrospective cohort analyses that were published prior to 2025-Feb-15 and met two key criteria: (1) administration of racemic (R,S) ketamine, esketamine, or arketamine to adult surgical patients, and (2) reporting of postoperative cognitive evaluation. Data points for each study include aspects of study design, patient demographic characteristics, surgical procedures, ketamine administration protocols, and the methods and outcomes of cognitive assessment.

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.

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)0.009
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0140.021
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0260.005

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 head0.050
GPT teacher head0.330
Teacher spread0.280 · 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 designSystematic review
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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