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Record W2416063719 · doi:10.1145/2901790.2901887

Heartefacts

2016· article· en· W2416063719 on OpenAlex
Jo Vermeulen, Lindsay MacDonald, Johannes Schöning, Russell Beale, Sheelagh Carpendale

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

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicEmotion and Mood Recognition
Canadian institutionsUniversity of Calgary
FundersFundação para a Ciência e a TecnologiaSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsComputer scienceCLIPSMultimediaHeartbeatMobile deviceSmartwatchHuman–computer interactionWorld Wide WebArtificial intelligenceWearable computerComputer security

Abstract

fetched live from OpenAlex

An increasing share of our daily interactions with others is mediated through mobile communication technologies. People communicate via text, emoticons, emojis and rich media such as video. We explore the design of Heartefacts, short video clips composed of highlights determined by heart rate changes while watching videos. Our survey investigated video sharing behaviour, and our feasibility study examined the possibility of detecting highlights in videos by monitoring people's heart rates measured with off-the-shelf wrist-worn sensors. Our results show that people do indeed have measurable responses with respect to their heartbeat patterns to six different emotions elicited by video clips. We compare video highlights verbally identified by our participants to physiological highlights as indicated by their heart rate data and also discuss and compare the automatically generated Heartefacts with video highlights created by an expert in video art. We close with design considerations for Heartefacts in mobile technology.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.980

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)0.0450.021

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 head0.050
GPT teacher head0.334
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

Quick stats

Citations15
Published2016
Admission routes2
Has abstractyes

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