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Record W2905569983 · doi:10.1037/cep0000158

A comparison of immediate serial recall and immediate serial recognition.

2018· article· en· W2905569983 on OpenAlexafffund
Chrissy M. Chubala, Ian Neath, Aimée M. Surprenant

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSerial position effectRecallSerial learningTask (project management)ConcretenessCognitive psychologyComputer scienceWord recognitionFree recallWord (group theory)Short-term memoryPsychologySpeech recognitionNatural language processingWorking memoryCognitionReading (process)MathematicsLinguisticsNeuroscience

Abstract

fetched live from OpenAlex

In an immediate serial recall task, participants are presented with a list of items that they must subsequently report back in the original presentation order. Although immediate serial recall has long been taken as the standard short-term and working memory task, a growing body of literature has instead made use of immediate serial recognition. In immediate serial recognition, a list of items is presented and subsequently represented, either in the exact same order or with two adjacent items swapped. Participants must decide whether the order of the list items was the same or different across the two presentations. Whereas serial recall and serial recognition are often treated as comparable tasks, with a few differences that make one or the other more suitable for a given experiment, the relationship between them has not been carefully examined. In this article, we report a series of experiments that directly compare the effects of various manipulations using the two tasks. In Experiments 1 and 2 we show an effect of word frequency in serial recall but not serial recognition. In Experiments 3 and 4 we show an effect of semantic relatedness in serial recall but not serial recognition. Experiments 5 and 6 demonstrate that the two tests are similarly affected by word concreteness and acoustic similarity, respectively. We consider the theoretical and methodological implications of these findings. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.368
Teacher spread0.261 · 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.

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

Citations13
Published2018
Admission routes2
Has abstractyes

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