Bibliographic record
Abstract
Torres, J. Checkers and Dot at the Beach. Illus. J. Lum. Toronto: Tundra Books, 2013. Print.The team of Ontario-based author and illustrator (and comics veterans) J. Torres and J. Lum brings young babies the duo of Checkers and Dot. Torres is best known for his Alison Dare graphic novels and other comics while this is graphic designer Lum’s first opportunity at illustrating for a children’s audience.Checkers, a young boy in a checkered shirt and his friend Dot, a little girl in a polka-dotted jumper are introduced as part of a larger series of Checkers and Dot titles, all with a high-contrasted and heavily-designed black and white motif. This high contrast design is said to appeal to young babies and toddlers as well as provide visual stimulation that may lead to increased brain development. The small size and sturdy binding is a plus.In Checkers and Dot on the Farm, the youngest of children are introduced to animal sounds in rhyming prose that will be fun for any parent or caregiver to read aloud. The images are highly stylized and will be mesmerizing to young children and the characters, a little reminiscent of anime, are quite cute. In Checkers and Dot at the Beach the concept of basic counting to 5 is introduced via ocean animals. Both volumes have a slight plot which makes it more palatable to adults.Though toddlers will enjoy re-reading these books to practice their farm animal sounds and basic counting, they may bore of the black and white in favour of more colourful & engaging board books aimed at preschoolers. The series is aimed at ages 0-4, however I feel it better suits the 0-2 age range. Suitable for public and home libraries.Recommended: 3 stars out of 4Reviewer: Debbie FeisstDebbie is a Public Services Librarian at the H.T. Coutts Education Library at the University of Alberta. When not renovating, she enjoys travel, fitness and young adult fiction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.057 |
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".