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Record W2798346558 · doi:10.14236/ewic/hci2017.103

Comparing a Scanning Ambiguous Keyboard to the On-screen QWERTY Keyboard

2017· article· en· W2798346558 on OpenAlex

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.

Bibliographic record

VenueElectronic workshops in computing · 2017
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsYork University
Fundersnot available
KeywordsText entryComputer scienceMode (computer interface)Word error rateCharacter (mathematics)Human–computer interactionComputer graphics (images)Speech recognitionMathematics

Abstract

fetched live from OpenAlex

This paper explores text entry on a scanning ambiguous keyboard (SAK) and the Windows on-screen keyboard (OSK) operating in scanning mode. The SPACEBAR was used for physical input with both keyboards. Testing involved 12 participants entering five phrases of text with each keyboard. On entry speed, the means were 5.06 wpm for the SAK and 2.67 wpm for the OSK, thus revealing a significant speed advantage for the SAK. However, the character-level error rate of 13.3% for the SAK was significantly higher than the error rate of 2.4% for the OSK. On subjective preference, 7 of 12 participants preferred the Windows OSK over the SAK, citing familiarity with the QWERTY layout as the most common reason. However, participants appreciated the efficiency of the SAK keyboard. A limitation of the results is the small amount of text entered.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0040.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.297
Teacher spread0.272 · 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