MétaCan
Menu
Back to cohort
Record W4383480984 · doi:10.1080/09658211.2023.2231672

Can synchronised tones facilitate immediate memory for printed lists?

2023· article· en· W4383480984 on OpenAlexfundno aff
Bailey Pannell, Dominic Guitard, Li Yu, Nelson Cowan

Bibliographic record

VenueMemory · 2023
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyRecallDistractionCognitive psychologyTone (literature)Linguistics

Abstract

fetched live from OpenAlex

In verbal list recall, adding features redundant with the ones to be recalled theoretically could assist recall, by providing additional retrieval cues, or it could impede recall, by draining attention away from the features to be recalled. We examined young adults' immediate memory of lists of printed digits when these lists were sometimes accompanied by synchronised, concurrent tones, one per digit. Unlike most previous irrelevant-sound effects, the tones were not asynchronous with the printed items, which can corrupt the episodic record, and did not repeat within a list. Memory of the melody might bring to mind the associated digits like lyrics in a song. Sometimes there were instructions to sing the digits covertly in the tone pitches. In three experiments, there was no evidence that these methods enhanced memory. Instead, there appeared to be a distraction effect from the synchronised tones, as in the irrelevant sound effect with asynchronised tones.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.302
Teacher spread0.230 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMemorySame topicMemory Processes and InfluencesFrench-language works237,207