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Record W1508671393

A Framework for Automated Evaluation of Hypertext Search Interfaces

2006· article· en· W1508671393 on OpenAlexafffund
Richard C. Bodner, Mark Chignell

Bibliographic record

VenueTexas Digital Library (University of Texas) · 2006
Typearticle
Languageen
FieldComputer Science
TopicInformation Retrieval and Search Behavior
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsComputer scienceHypertextFocus (optics)Search engineExploratory analysisInformation retrievalHuman–computer interactionWorld Wide WebData science
DOInot available

Abstract

fetched live from OpenAlex

An evaluation framework and simulator of an interactive information retrieval system is introduced. The simulation environment implements a model of an interactive information retrieval system that uses an adaptive hypertext interface to present documents to the user. Links within such an interface are generated at runtime based on previous link selections. In addition to the model of the hypertext interface, several agents have been implemented which embody prototypical information exploration styles for such an interactive information retrieval interface. The simulation environment is designed to allow researchers to conduct exploratory investigations that can help to narrow the focus of future human subject studies by showing which differences in information exploration style and functionality within the interface or underlying search algorithms that are likely to produce significant differences in future human subject studies. An experiment was carried out to demonstrate how the simulation environment could be used to predict performance when using different search strategies in a dynamic hypertext

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 categoriesnone
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 score0.737
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.034
GPT teacher head0.255
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2006
Admission routes2
Has abstractyes

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