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Record W2059354418 · doi:10.1145/2254556.2254686

Spalendar

2012· article· en· W2059354418 on OpenAlexaff
Xiang Chen, Sebastian Boring, Sheelagh Carpendale, Anthony Tang, Saul Greenberg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEvent (particle physics)Computer scienceVisualizationSpace (punctuation)Human–computer interactionSortingMultimediaWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Portable paper calendars (i. e., day planners and organizers) have greatly influenced the design of group electronic calendars. Both use time units (hours/days/weeks/etc.) to organize visuals, with useful information (e.g., event types, locations, attendees) usually presented as - perhaps abbreviated or even hidden - text fields within those time units. The problem is that, for a group, this visual sorting of individual events into time buckets conveys only limited information about the social network of people. For example, people's whereabouts cannot be read 'at a glance' but require examining the text. Our goal is to explore an alternate visualization that can reflect and illustrate group members' calendar events. Our main idea is to display the group's calendar events as spatiotemporal activities occurring over a geographic space animated over time, all presented on a highly interactive public display. In particular, our Spalendar (Spatial Calendar) design animates people's past, present and forthcoming movements between event locations as well as their static locations. Detail of people's events, their movements and their locations is progressively revealed and controlled by the viewer's proximity to the display, their identity, and their gestural interactions with it, all of which are tracked by the public display.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations9
Published2012
Admission routes1
Has abstractyes

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