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dc.contributor.authorMeylan, Stephan C.
dc.contributor.authorGriffiths, Thomas L.
dc.date.accessioned2022-02-18T19:50:41Z
dc.date.available2022-02-18T19:50:41Z
dc.date.issued2021-06
dc.identifier.issn0364-0213
dc.identifier.issn1551-6709
dc.identifier.urihttps://hdl.handle.net/1721.1/140541
dc.languageen
dc.publisherWileyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1111/cogs.12983en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceWileyen_US
dc.titleThe Challenges of Large‐Scale, Web‐Based Language Datasets: Word Length and Predictability Revisiteden_US
dc.typeArticleen_US
dc.identifier.citationMeylan, Stephan C. and Griffiths, Thomas L. 2021. "The Challenges of Large‐Scale, Web‐Based Language Datasets: Word Length and Predictability Revisited." Cognitive Science, 45 (6).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences
dc.relation.journalCognitive Scienceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2022-02-09T20:16:12Z
mit.journal.volume45en_US
mit.journal.issue6en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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