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Record W2946797438 · doi:10.5210/jbc.v43i1.7874

Usability Guidelines for an Online Image Database

2019· article· en· W2946797438 on OpenAlex
Ruth Chang, Donald F. Bliss, Anne Altemus

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 Biocommunication · 2019
Typearticle
Languageen
FieldComputer Science
TopicImage Retrieval and Classification Techniques
Canadian institutionsUniversity of Toronto
FundersU.S. National Library of MedicineNational Institutes of Health
KeywordsUsabilityNavigabilityComputer scienceInformation retrievalSet (abstract data type)DatabaseAuditWorld Wide WebHuman–computer interactionBusiness

Abstract

fetched live from OpenAlex

There are currently no existing guidelines for optimizing user experience in online image databases. Here we use established usability design principles to develop a set of 50 recommendations for improving database organization, navigability, and search functionality. We conduct a resource audit of commercial and non-profit image galleries and evaluate them upon our criteria. Our findings are summarized within a basic wireframe to be used as reference for prospective image databases in the future.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.310
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0020.000
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 head0.189
GPT teacher head0.414
Teacher spread0.224 · 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