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Record W4386543511 · doi:10.7146/pl.v14i2.135876

Symbolic forms and cognition

2023· article· en· W4386543511 on OpenAlexaff
Chang Hong Liu, John M. Kennedy

Bibliographic record

VenuePsyke & Logos · 2023
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsTask (project management)Matching (statistics)RecallCognitionDegree (music)Cognitive psychologyPsychologyComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

Two shapes - a cire le and a square - are used to study the effects of form symbolism in cognitive tasks. The first experiment examines the degree of consensus between subjects matching a list of pairs of words with the pair of shapes. The second experiment examines the correlation between the degree of consensus and the reaction times required in the matching task. The third experiment examines the effect of the consensus on performance on a recall task. The findings indicate there is significant consensus between subjects in tasks assessing form symbolism, the amount of consensus predicts reaction time on the matching task and the amount of consensus also predicts performance on the memory task.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.006
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.263
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations9
Published2023
Admission routes1
Has abstractyes

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