Bibliographic record
Abstract
Buchholz, Rachel. True Love: 24 Surprising Stories of Animal Affection. Washington: National Geographic, 2013. Print.True Love is a short gift book, meant as a Valentine’s Day gift book, filled with twenty-four stories about love between animals and accompanied by beautiful National Geographic photographs. These stories are generally less than a page long, and cover family ties between animals, including siblings, and parents, to friendship, and love. Animals featured in these stories include domestic animals such as dogs, pigs, ducks, sheep and donkeys, but also wild animals such as whales, flamingos, and elephants. Sometimes the stories are about farm animals, animals in the wild, or zoo animals.Rachel Buchholz, the author of the book, is the executive editor of National Geographic Kids and National Geographic Little Kids magazines. These stories were collected over the course of her fifteen years working in editing. The images are all taken by National Geographic photographers. Some of the images are actually of the animals in the stories, while other images are just the same species as those in the stories.True Love was designed as a gift book, and it truly embraces the format. Even though it is a picture book, the text might be long for some children to read through patiently. Each story is exemplified by only one picture. The language used is easily understood, however, and the beautiful photographs of adorable animals will draw readers. As the material deals with themes of family, love, and friendships, this is a book that many children will enjoy reading with their families.Recommended: 3 out of 4 starsReviewer: Colette LeungColette Leung is a graduate student at the University of Alberta, working in the fields of Library and Information science and Humanities Computing who loves reading, cats, and tea. Her research interests focus around how digital tools can be used to explore fields such as literature, language, and history in new and innovative ways.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".