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Record W2516909152 · doi:10.20982/tqmp.11.2.p089

The Recording and Quantification of Event-Related Potentials: I. Stimulus Presentation and Data Acquisition

2015· article· en· W2516909152 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Quantitative Methods for Psychology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStimulus (psychology)Event-related potentialScalpElectroencephalographyPsychologyCognitionComputer scienceCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Event-related potentials (ERPs) are the changes in the ongoing electrical activity of the brain (the EEG) that are elicited by either an external physical stimulus or an internal psychological "event". This article provides a tutorial review of the methods used for the collection of ERP data. Because ERPs are influenced by both stimulus parameters and the mental state of the subject (what the subject is "doing"), precise control over how the stimulus is presented and how the subject's response is monitored must be described. ERPs are generally recorded from electrodes placed on the scalp. How the electrodes are placed (the montage) and the choice of the reference to which the electrical activity of the scalp are compared will have a large influence on the results. Electrodes will also pick up extraneous artifact or "noise". Methods to reduce this noise are described. ERPs provide high temporal resolution of the extent of information processing allowing researchers to access to both sensory and cognitive processes involved in complex decision-making.

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.

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)0.005
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.698
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.332
GPT teacher head0.551
Teacher spread0.219 · 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