Bibliographic record
Abstract
Dear Readers, We are delighted to recommend a diverse group of children’s books for your reading pleasure. Remarkably, more than half of the books in this issue were “highly recommended” by Deakin reviewers, so I wanted to take this opportunity to explain the significance of a 4-star rating. Our reviewers are looking for books with captivating stories from start to finish that are worthy of reading over and over. Many of the books we review are illustrated, so we also pay close attention to the artful marriage of words and pictures. A four-star rating demands excellence in the book’s design and writing quality, and of course, the book should have a story that inspires readers to think and learn. It certainly isn’t easy to earn a 4-star review from our reviewers, and for that reason, I would like to congratulate the authors, illustrators, and publishing teams who produced the eight books that earned a 4-star rating in this issue: Cheerful Chick, Down by the River, Gluten Free is Part of Me, Here Comes Rhinoceros, That’s Not Hockey, Una Huna?: What Is This?, What’s My Superpower?, and You Hold Me Up. The creators of these excellent books deserve commendation for a job well done, and we owe them our thanks for capturing our interest and imagination. I am thrilled to see so many books recommended by Deakin reviewers for their overall quality and I hope you’ll find something in this issue to fire your imagination. Happy reading! Robert Desmarais, Managing Editor
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.195 | 0.274 |
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".