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Record W4230687468 · doi:10.1002/asi.20786

Controlled user evaluations of information visualization interfaces for text retrieval: Literature review and meta‐analysis

2008· article· en· W4230687468 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

VenueJournal of the American Society for Information Science and Technology · 2008
Typearticle
Languageen
FieldComputer Science
TopicData Visualization and Analytics
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceUsabilityInformation retrievalVisualizationSet (abstract data type)Subject (documents)Information visualizationWorld Wide WebHuman–computer interactionData mining

Abstract

fetched live from OpenAlex

Abstract This review describes experimental designs (users, search tasks, measures, etc.) used by 31 controlled user studies of information visualization (IV) tools for textual information retrieval (IR) and a meta‐analysis of the reported statistical effects. Comparable experimental designs allow research designers to compare their results with other reports, and support the development of experimentally verified design guidelines concerning which IV techniques are better suited to which types of IR tasks. The studies generally use a within‐subject design with 15 or more undergraduate students performing browsing to known‐item tasks on sets of at least 1,000 full‐text articles or Web pages on topics of general interest/news. Results of the meta‐analysis ( N = 8) showed no significant effects of the IV tool as compared with a text‐only equivalent, but the set shows great variability suggesting an inadequate basis of comparison. Experimental design recommendations are provided which would support comparison of existing IV tools for IR usability testing.

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)0.002
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.005
Open science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.355
Teacher spread0.328 · 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