Bibliographic record
Abstract
McGowan, Jayme. One Bear Extraordinaire. Abrams Books for Young Readers, 2015.This picture book is a story about a bear who begins the tale as a “one man band”, playing a guitar, drum, cymbals, harmonica and tambourine. Although legendary in the forest, he feels that, “something is missing”, so he sets out to find it. As he journeys, other animals join him, but none of them fill the void. Eventually the group encounters Wolf Pup, who wants to join but has no instrument. Bear offers him several of his instruments, but he just chews them. Finally, Wolf Pup howls at the moon and Bear realizes that what his song needed was a singer. In the end Bear just has his guitar left, but he has four other band members and their tune “sounded just right.” There are two music messages in this book. First, being a solo performer is fine, but making music with others is fine, too. The second message is that everyone has something to contribute, if they are just given a chance. McGowan’s technique for creating pictures is unusual. She builds up layers of paper, and then photographs the image. Children will enjoy identifying objects and creatures in the brightly coloured pictures. This is a good book and should be included in public libraries and school libraries.Recommended: 3 stars out of 4Reviewer: Sean BorleSean Borle is a University of Alberta undergraduate student who is an advocate for child health and safety.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.258 | 0.172 |
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".