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Record W4210289154 · doi:10.3389/fnrgo.2021.751354

An Exploratory Study of Physiological Linkage Among Strangers

2022· article· en· W4210289154 on OpenAlex
Savannah Boyd, Ashley Kuelz, Elizabeth Page‐Gould, Emily A. Butler, Chad Danyluck

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Neuroergonomics · 2022
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsCarleton UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLinkage (software)Exploratory researchPsychologyBiologyGeneticsSociologyGeneAnthropology

Abstract

fetched live from OpenAlex

The present study explores physiological linkage (i.e., any form of statistical interdependence between the physiological signals of interacting partners; PL) using data from 65 same-sex, same ethnicity stranger dyads. Participants completed a knot-tying task with either a cooperative or competitive framing while either talking or remaining silent. Autonomic nervous system activity was measured continuously by electrocardiograph for both individuals during the interaction. Using a recently developed R statistical package (i.e., rties ), we modeled different oscillatory patterns of coordination between partner's interbeat interval (i.e., the time between consecutive heart beats) over the course of the task. Three patterns of PL emerged, characterized by differences in frequency of oscillation, phase, and damping or amplification. To address gaps in the literature, we explored (a) PL patterns as predictors of affiliation and (b) the interaction between individual differences and experimental condition as predictors of PL patterns. In contrast to prior analyses using this dataset for PL operationalized as covariation, the present analyses showed that oscillatory PL patterns did not predict affiliation, but the interaction of individual differences and condition differentially predicted PL patterns. This study represents a next step toward understanding the roles of individual differences, context, and PL among strangers.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.058
GPT teacher head0.342
Teacher spread0.284 · 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