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Record W4205376988 · doi:10.1002/wcs.1323

Pupillometry

2014· article· en· W4205376988 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWiley Interdisciplinary Reviews Cognitive Science · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersCanada Research Chairs
KeywordsPupillometryCognitionPsychologyPerceptionCognitive sciencePupilCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

UNLABELLED: Pupillometry is the study of changes in the diameter of the pupil as a function of cognitive processing. This review paper provides a brief historical overview of the study of pupillometry in cognitive science. The physiology of pupillary responses is introduced, leading to an outline of early pupillometry work, which began with the seminal work of Hess and Polt in the 1960s. The paper then presents a broad review of contemporary research in cognitive sciences that relies on pupillometry. This review is organized around five general domains, namely perception, language processing, memory and decision making, emotion and cognition, and cognitive development. In order to illustrate the nature of the method, and the challenges of analysis, the next section of the review details the process of compiling, processing, and analyzing data from a simple, typical pupillometry study. WIREs Cogn Sci 2014, 5:679-692. doi: 10.1002/wcs.1323 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.168
GPT teacher head0.443
Teacher spread0.275 · 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