Bibliographic record
Abstract
Reviewed by: Dog Poems Deborah Stevenson Crawley, Dave Dog Poems; illus. by Tamara Petrosino. Wordsong/Boyds Mills, 2007 [32p] ISBN 978-1-59078-454-9$16.95 Reviewed from galleys Ad Gr. 3-5 Two dozen doggy verses treat canine subjects such as domestication ("Wolf Dog"), expression ("Telling a Tail"), mishaps ("Wrong Kitty" and "Oops"), and breed identity ("Basset," "No Beautiful Bulldogs," "The Labrador Loves Liquid"). Though Crawley relies a bit much on jingly anapestic meter, the verses possess an abundance of kid-friendly humor enhanced by true and knowledgeable appreciation of their subject ("Snowball," for instance, describes the way Dalmatian puppies start out snow white and then gradually acquire their spots). Unfortunately, the poems are undercut by stodgy design and by line-and-watercolor illustrations that have the slick, samey cheer of advertising graphics rather than any depth of character. Readers will therefore be much better off with MacLachlan's deliciously doggy Once I Ate a Pie (BCCB 6/06), but there's flavor enough in the verse here to give Fido fans a little literary something to chew on. Copyright © 2007 The Board of Trustees of the University of Illinois
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.029 |
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".