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Record W2793532917 · doi:10.20361/g2r69z

A Bedtime Yarn by N. Winstanley

2018· article· en· W2793532917 on OpenAlexvenueaboutno aff
Janice Kung

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInterdisciplinary Cultural and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDreamYarnAdventureArtBluesSurpriseVisual artsArt historyPsychologyEngineering

Abstract

fetched live from OpenAlex

Winstanley, Nicola. A Bedtime Yarn, illustrated by Olivia Chin Mueller, Tundra Books, 2017.This picture book explores the dreams of Frankie, a little bear who has trouble falling asleep at night. To help him sleep, his mother provides a ball of yarn for him to hold while she works on the other end, knitting a special surprise for Frankie. Each ball of yarn is a different colour with its own story that takes the young bear on incredible adventures. For instance, a sea-green yarn invokes a dream that takes him deep into underwater caverns and a brown yarn reminds him of cake as a result of his upcoming birthday celebrations. Every colour depicts a new dream and unique experience. The story concludes with Frankie’s mother surprising him with a multi-coloured blanket that was made from all the different colours of yarn that he held. Beautiful artwork illustrated by Olivia Chin Mueller accompanies the story, including strands of coloured yarn that surround the images. The author creatively used colour as the starting off point for representing the wide variety of dreams that the little bear encounters. This children’s book teaches readers about different colours and the imaginative element of dreams. This book is suitable for children from Kindergarten to Grade 2. Recommended: 3 out of 4 starsReviewer: Janice KungJanice Kung is a Public Services Librarian at the University of Alberta, John W. Scott Health Sciences Library. She obtained her undergraduate degree in commerce and completed her MLIS degree in 2013. She believes that the best thing to beat the winter blues is to cuddle up on a couch and lose oneself in a good book.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.312
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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