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Record W2416497839 · doi:10.1016/j.dib.2016.05.061

Data on the impact of SSRIs and depression symptoms on the neural activities in obsessive–compulsive disorder at rest

2016· article· en· W2416497839 on OpenAlexaff
Yunhui Chen, Michal Juhás, Andrew J. Greenshaw, Qiang Hu, Xin Meng, Hongsheng Cui, Yongzhuo Ding, Lu Kang, Yubo Zhang, Yuhua Wang, Guangcheng Cui, Ping Li

Bibliographic record

VenueData in Brief · 2016
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of Alberta
FundersDepartment of Education, Heilongjiang Province
KeywordsObsessive compulsiveDepression (economics)Rest (music)Neural correlates of consciousnessResting state fMRIPsychologyPsychiatryNeural activityClinical psychologyMedicineNeuroscienceInternal medicineCognition

Abstract

fetched live from OpenAlex

The data provided here related to our research article (Chen et al., 2016) [1]. We provide whole-brain intrinsic functional connectivity patterns in obsessive-compulsive disorder at resting-state [1]. This article also provides supplementary information to our research article, i.e., between - group comparisons of the effect of selective serotonin reuptake inhibitors (SSRIs) and combined depression symptoms on resting-state neural activities in obsessive-compulsive disorder. The data presented here provide novel insights into the effect of SSRIs and combined depression symptoms on the neural activities at rest.

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)0.000
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.083
GPT teacher head0.325
Teacher spread0.242 · 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
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

Citations4
Published2016
Admission routes1
Has abstractyes

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