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Record W3146515045 · doi:10.36106/gjra/0402063

NORMATIVE DATA OF COGNITIVE ASSESSMENT BY AUDITORY P300 EVENT RELATED POTENTIAL, MONTREAL COGNITION ASSESSMENT AND CHOICE REACTION TIME AND ITS VARIATION WITH AGE AND GENDER IN UTTARAKHAND REGION OF INDIA.

2021· article· en· W3146515045 on OpenAlexaboutno aff
Sunita Mittal, Akriti Kapila, Ashwini A Mahadule, Prashant Patil, Arun Goel, Rajesh Kathrotia, Latika Mohan

Bibliographic record

VenueGLOBAL JOURNAL FOR RESEARCH ANALYSIS · 2021
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionNormativeEvent-related potentialAudiologyPsychologyCognitive testCognitive impairmentDemographyDevelopmental psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Background: Tests like auditory P300 event related potential, neuro-psychometric pen pencil Montreal Cognition Assessment Test (MOCA) and Choice reaction time have been used as indexes of cognitive function. Thus this study has been planned with the aim to evaluate cognitive ability of a normal adult to nd out normative data and its, variation with age and gender in Uttarakhand region of India. Materials and Method: This cross-sectional study was carried out in the department of Physiology of AIIMS, Rishikesh on 52 healthy with ages ranging from 20 to 40 years, equal number of male & female volunteers with the ability to understand test procedures. Following tests were performed in the given order for uniformity during 11-1 pm timing of a day: 1. Event Related Potential-P300 2. Neuro-psychometric assessment (Hindi Montreal Cognitive Assessment -HMOCA test) and 3. Choice Reaction Time. Results and Conclusion: Mean of P300 Latency is 310 ± 37.14 msec, mean of P300 Amplitude is 14 ± 7.5 uv (from Cz electrode site), mean of Montreal Score is 24.81±3.25, and mean of CRT is 584.5 ±84.06 ms in all the subjects. All the parameters are better in younger age group. All the parameters are better in male except MOCA score

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.077
GPT teacher head0.420
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueGLOBAL JOURNAL FOR RESEARCH ANALYSISSame topicEEG and Brain-Computer InterfacesFrench-language works237,207