Bibliographic record
Abstract
Mixter, Helen. The Dog. Illustrated by Margarita Sada. Greystone Books, 2017. In The Dog, Helen Mixter has kept her text brief and simple, and allowed the images to convey the story. It is a story about a boy who is ill and how much his quality of life is improved by the introduction of a therapy dog. Margarita Sada’s artwork easily shows the fatigue, sadness and illness of the boy and the unconditional affection of the dog. The dog, who looks like a young golden retriever, is never given a name, perhaps to keep her more generic. She is depicted as having boundless health and energy. She even has rosy cheeks, indicating health. The colours that Sada uses are bright and natural and the pictures will attract and hold the attention of small children. Inspired by a visit to a Vancouver children’s hospice the book gently presents how effective a therapy dog can be for very sick children. The Dog would be a good addition to public and school libraries. It would also be an excellent addition to libraries in children’s hospitals. Highly recommended: 4 stars out of 4 Reviewer: Sandy Campbell Sandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.362 | 0.276 |
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".