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Record W2137646703 · doi:10.1177/2158244013489687

Alpha Meals

2013· article· en· W2137646703 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

VenueSAGE Open · 2013
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlphanumericOptimal distinctiveness theoryRecallHomogeneousComputer scienceCognitive loadSet (abstract data type)Task (project management)Code (set theory)CognitionPsychologyCognitive psychologySocial psychologyMathematicsEngineeringOperating system

Abstract

fetched live from OpenAlex

Past research suggests that our ability to recall information increases when atypical items are presented within otherwise homogeneous sets. We investigated whether this effect applied to performance on practical, everyday tasks. In a computer-simulated restaurant scenario, participants acted as virtual servers, delivering “plates of food orders” to tables set up in different “rooms.” Plate destination was communicated using either a distinctive alphanumeric code or a homogeneous numeric code, both of which indicated the room and table number for delivery of food orders. We examined accuracy of plate delivery when two (low load) or three (high load) coded assignments were given per delivery trial. As expected, performance declined from the low- to high-load condition. Importantly, performance declined less with alphanumeric compared with all-numeric communication of assignments. Results suggest that increasing the distinctiveness of assignments, by using alphanumeric codes, can boost performance in real-life situations to significantly improve memory-related task performance, particularly when cognitive load is taxed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0640.032

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 head0.055
GPT teacher head0.402
Teacher spread0.348 · 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