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Record W3166960372 · doi:10.31234/osf.io/3ydqr

Voluntary Switching of Visual Motion Rivalry Estimate Human Heart Rate

2021· preprint· en· W3166960372 on OpenAlexaff
Ahmad Yousef

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBinocular rivalryHeart rateStimulus (psychology)PsychologyRespiratory ratePerceptionRivalryBreathingVisual perceptionAudiologyCognitive psychologyMedicineNeuroscienceBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

We showed that deep breathing and voluntary hand movements are able to effectively and timely alter visual bistable perception, see reference 1 and 2. Deep breathing and voluntary hand movements require cognitive control, however, deep breathing causes stable respiratory sinus arrythmia (RSA). We decided to achieve this study because we have previously claimed that the RSA process is the governor of the visual motion rivalry through the deep breathing, see reference 1. We therefore suspect whether every kind of volitional switching to visual motion rivalry has correlation to the heart rate. Expectedly, we found that deep inhalation which is associated with the perception of the actual visual martial is able to increase the heart rate; and deep expiration which is correlated to the perception of motion reversals is able to decrease the heart rate. Astoundingly, for the voluntary switching through the hand movements, we found that when the human subjects move a pen in harmony with the actual physical direction which results in the perception of the original materials of the visual stimulus; the heart rate is increased. Illusory motion reversals, which appears when the pen is moved in the opposite direction of the actual motion, are correlated to heart rate deceleration!

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.333
Teacher spread0.310 · 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
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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