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Record W4393021736 · doi:10.1101/2024.03.18.24304375

WITHDRAWN: The Impact of Cognitive Function on Health-Related Quality of Life in Persons with Post-COVID-19 Condition: A Randomized Controlled Trial on Vortioxetine

2024· preprint· en· W4393021736 on OpenAlexaff
Angela T.H. Kwan, Moiz Lakhani, Gia Han Le, Gurkaran Singh, Kayla M. Teopiz, Ziji Guo, Arshpreet Singh Manku, Joshua D. Rosenblat, Roger S. McIntyre

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsBrain and Cognition Discovery FoundationUniversity of Ottawa
Fundersnot available
KeywordsVortioxetineCoronavirus disease 2019 (COVID-19)Randomized controlled trialCognitionQuality of life (healthcare)Medicine2019-20 coronavirus outbreakPsychologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Physical medicine and rehabilitationGerontologyClinical psychologyPsychiatryPsychotherapistVirologyInternal medicineMajor depressive disorder

Abstract

fetched live from OpenAlex

Withdrawal Statement The authors have withdrawn this manuscript because substantial changes have been made to the study, including multiple additional subgroup analyses that significantly alter the scope and interpretation of the findings. Therefore, the authors intend to prepare and submit a revised version as a new manuscript. As such, they do not wish this work to be cited as a reference for the project. If you have any questions, please contact the corresponding author.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0500.005

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 head0.033
GPT teacher head0.360
Teacher spread0.327 · 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 designRandomized trial
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

Citations0
Published2024
Admission routes1
Has abstractyes

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