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Record W2063264935 · doi:10.1080/01690965.2010.511475

Frequency effects in the production of Dutch deverbal adjectives and inflected verbs

2010· article· en· W2063264935 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.

Bibliographic record

VenueLanguage and Cognitive Processes · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLinguisticsMorphemeMental lexiconMathematicsNounPsychologyPhilosophy

Abstract

fetched live from OpenAlex

In two experiments, we studied the role of frequency information in the production of deverbal adjectives and inflected verbs in Dutch. Naming latencies were triggered in a position–response association task and analysed using stepwise mixed-effects modelling, with subject and word as crossed random effects. The production latency of deverbal adjectives was affected by the cumulative frequencies of their verbal stems, arguing for decomposition and against full listing. However, for the inflected verbs, there was an inhibitory effect of Inflectional Entropy, and a nonlinear effect of Lemma Frequency. Additional effects of Position-specific Neighbourhood Density and Cohort Entropy in both types of words underline the importance of paradigmatic relations in the mental lexicon. Taken together, the data suggest that the word-form level does neither contain full forms nor strictly separated morphemes, but rather morphemes with links to phonologically and—in case of inflected verbs—morphologically related word forms.

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)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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)0.0000.000

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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