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Record W2899292286 · doi:10.1145/3267305.3274111

Pseudo-Ambience

2018· article· en· W2899292286 on OpenAlexafffund
Jeffrey R. Blum, Jeremy R. Cooperstock, Jessica R. Cauchard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMitacsFaculty of Engineering, McGill University
KeywordsComputer scienceHaptic technologyHuman–computer interactionModalitiesFocus (optics)Context (archaeology)Mobile deviceMultimediaArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

A hallmark of ambient displays is their constant presence in the periphery of the user's attention, such as the Ambient Orb1 that changes color based on the outdoor weather. Users of such a device can explicitly turn their attention to the device if they are curious about the current weather conditions, and also be notified of a change by noticing the light changing abruptly, e.g., as a thunderstorm suddenly begins. However, especially in a mobile context, it can be difficult to have truly continuous indicators that are not fatiguing, annoying, or consuming considerable power. We propose "pseudo-ambient" displays that are not continuous, yet are nearly always accessible since they are triggered at regular intervals. Our contention is that such displays can potentially provide most of the benefits of a fully continuous ambient display, with limited drawbacks. In this work we focus on haptic pseudo-ambient displays. Yet, we believe the same approach can apply to other modalities, such as visual and audio.

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 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.022

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 head0.396
GPT teacher head0.487
Teacher spread0.091 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations3
Published2018
Admission routes2
Has abstractyes

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