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Record W2010022183 · doi:10.1080/17453050802398702

Using the Principles of Interactive Cartography to Communicate the Mechanisms of Migraine Pain

2008· article· en· W2010022183 on OpenAlexaff
Ardis Cheng, Linda Wilson‐Pauwels, David Mazierski, Shelley L. Wall

Bibliographic record

VenueJournal of Visual Communication in Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZoomThink aloud protocolUsabilityComprehensionHuman–computer interactionMigraineComputer scienceOrientation (vector space)PsychologyMultimediaEngineering

Abstract

fetched live from OpenAlex

The program entitled 'Mapping Migraine Pain' was created based on the principles of interactive cartography to communicate the complexity of the mechanisms of migraine pain. An innovative zoom slider was developed to enhance spatial orientation and comprehension of multiple scales of information from the anatomical to the cellular and molecular levels. Think-aloud protocols were conducted with ten undergraduate first-year medical students to evaluate the significance and usability of the program. The zoom slider, based on interactive cartography, proved to be an effective and intuitive navigational element.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.179
GPT teacher head0.422
Teacher spread0.243 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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