Bibliographic record
Abstract
Ohmura, Tomoko. The Long, Long Line. Toronto, ON: OwlKids Books, 2013. Print."Thank you for waiting, and welcome aboard! One at a time, please!" mentions the bird, who is the ride guide on this mysterious ride for which 50 different animals have patiently lined up. As they wait, the bird flies amongst them, offering reassuring words as they guess as to what they may be in line for and play word games to pass the time. The anticipation builds, and finally they start boarding the ride, which turns out to be a very large whale on which the animals ride while the whale performs somersaults, dives and sprays. Children will be delighted by all 50 animals represented on the large gatefold spread in the center of the book, from the smallest frog to the largest elephant.Children will love the small details such as the tail of the next animal in line ‘peeking’ around the corner of the page and the size of the animals increasing as they get closer to the ride giving perspective of size. A list of all 50 animals is included at the back for easy reference when young readers get stumped by a species. While this is indeed a picture book aimed at young children it is no quick read – children will want to hear every word of the animals’ conversations as they wait and will want to count as they go, and likely once all the animals are aboard the whale they will want to confirm there are indeed 50 animals present, perhaps multiple times.The colourful illustrations by the author are cute and engaging and show a wide range of expressions and interplay between the animals. The language felt slightly unnatural but this may be a result of this edition being a translation of the original Japanese work Nanno Gyoretsu? A fun book for public and elementary schools as well as a nice addition to science or math based storytime in lower elementary grades.The Long, Long Line was selected as one of the best children’s books of 2013 by Kirkus Reviews.Recommended: 3 out of 4 stars Reviewer: 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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.376 | 0.344 |
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".