Bibliographic record
Abstract
Baker, Darryl. Kamik Joins the Pack. Illustrated by Qin Leng. Inhabit Media, 2016.This is the third book about Jake and his puppy, Kamik. Each of the books in the series is adapted from the memories of a different author. The first, Kamik: an Inuit Puppy Story was by Donald Uluadluak, while Kamik’s First Sled was by Matilda Sulurayok. In addition to the characters and setting, the constant across these books is the illustration by Qin Leng, whose bright and colourful drawings capture the Arctic environment. Each of Leng’s drawings covers a pair of pages, with text overprinted on the snow or sky. Leng sometimes cleverly adds to the expansiveness of the images by showing just a boot or a dog entering or exiting the side or bottom of the page. In this volume Jake and the reader learn about looking after sled dogs and training a puppy to join a dogsled team. Jake’s uncle teaches him about cutting dogs’ nails, inspecting paws for injuries, mending harnesses, building dog houses and keeping dogs healthy. The most important lesson is about spending time with the dogs to get to know them well. The language is more appropriate to an upper elementary reading level than the 5 to 7 year-old intended audience. However, because it is primarily a picture book, it would be a good read-aloud book for younger audiences.Recommended for elementary schools and public libraries.Highly Recommended: 4 stars out of 4Reviewer: Sandy CampbellSandy 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.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.436 | 0.334 |
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".