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Record W3202976381 · doi:10.1007/s12671-021-01764-9

Enhancing Cognition in Older Persons with Depression or Anxiety with a Combination of Mindfulness-Based Stress Reduction (MBSR) and Transcranial Direct Current Stimulation (tDCS): Results of a Pilot Randomized Clinical Trial

2021· article· en· W3202976381 on OpenAlexafffund
Heather Brooks, Hanadi Ajam Oughli, Lojine Kamel, Subha Subramanian, Gwen Morgan, Daniel M. Blumberger, Jeanne Kloeckner, Sanjeev Kumar, Benoit H. Mulsant, Eric J. Lenze, Tarek K. Rajji

Bibliographic record

VenueMindfulness · 2021
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsToronto Dementia Research AllianceCentre for Addiction and Mental HealthUniversity of Toronto
FundersTaylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine in St. LouisNational Institutes of HealthUniversity of TorontoOntario Ministry of Health and Long-Term CareCanadian Institutes of Health ResearchCentre for Addiction and Mental Health FoundationWeston Brain InstituteBrightFocus FoundationMcKnight FoundationEli Lilly and CompanyNational Alliance for Research on Schizophrenia and DepressionJazz PharmaceuticalsEvelyn F. McKnight Brain Research FoundationIndiviorBrain Research FoundationOntario Ministry of Research and InnovationH. Lundbeck A/SPatient-Centered Outcomes Research InstituteFondation Brain CanadaNational Institute of Mental HealthPfizer
KeywordsMindfulnessTranscranial direct-current stimulationMindfulness-based stress reductionAnxietyPsychologyRandomized controlled trialClinical psychologyDementiaCognitionPsychiatryMedicineStimulationDiseaseInternal medicine

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)0.001
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.331
Teacher spread0.282 · 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

Citations38
Published2021
Admission routes2
Has abstractno

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