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Record W2101307329 · doi:10.1109/hicss.2003.1174245

PDA access to Internet content: focus on forms

2003· article· en· W2101307329 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceWorld Wide WebFocus (optics)Transformation (genetics)Context (archaeology)Web pageThe InternetMobile deviceWeb contentWeb modelingTask (project management)MultimediaPerspective (graphical)Human–computer interactionEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Many Web applications in business, personal finances, medicine, sales, and education, are ideal scenarios for the integrated use of different devices, both wired and wireless. From the user's perspective, accessing Web content using multiple devices is not enough, there needs to be continuity of task focus and recognition that each device has particular characteristics. In earlier work, we concentrated on dynamic transformation of text, lists, and tables found in Web pages and in this paper we examine specifically the transformation of forms for use on small screens. This means, for example, that a user can deal with a complex form on a small screen in a mobile setting, can begin to fill out a form on one machine and complete it on another, or can fill in a form in a collaborative context. Our algorithm has a success rate of over 90% in the transformation of forms occurring in Web pages into forms suited for small screens.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.728

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.069
GPT teacher head0.287
Teacher spread0.218 · 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

Citations8
Published2003
Admission routes1
Has abstractyes

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