Bibliographic record
Abstract
Buzzeo, Toni, and David Small. One Cool Friend. New York : Dial Books for Young Readers, 2012. Print. Hailing from Michigan, former teacher and children’s librarian Toni Buzzeo has been writing children’s literature since 1995. Ms. Buzzeo has published over 20 picture books and has written or co-written curriculum support materials and professional books for teachers and teacher librarians. One Cool Friend was named a 2013 Caldecott Honor book. Eliot, “a very proper young man” politely asks his father, “May I have a penguin?” His father acquiesces and Eliot takes home a unique memento of his visit to the aquarium. A humorous and unexpected adventure unfolds as Magellan, Eliot’s new pet penguin, gets settled in his new home. The interactions between Eliot and his father are entertaining and full of double meaning. David Small’s clever illustrations and strategic use of colour and texture provide hints to the surprise ending. Although targeted at children aged 5-9, readers of all ages will enjoy this book, gleaning different meanings from the illustrations and text. This story invites repeated readings; readers are sure to pick up details that they missed previously. Highly recommended: 4 out of 4 stars Reviewer: Maria Tan Maria is a Public Services Librarian at the University of Alberta’s H. T. Coutts Education Library. She enjoys travelling and visiting unique and far-flung libraries. An avid foodie, Maria’s motto is, “There’s really no good reason to stop the flow of snacks”.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.213 | 0.161 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".