Bibliographic record
Abstract
Goodnight World: Animals of the Native Northwest. Vancouver: Native Explore/Garfinkel Publications, 2012. Print.The book I chose is called Goodnight World – Animals of the Native Northwest. The book has various authors but it was published in 2012 by Native Northwest.The book is about saying goodnight to different animals like bears, owls, wolverines, frogs, butterflies and turtles. The book also shows many works of Art of the animals that we are saying goodnight to.I loved the moon and sun pictures in the background on every page. I loved the picture of the octopus because it has the arms of an octopus and the head of an eagle. The book was easy to read and the pictures were amazing.I wish the book was longer, had more animals in it and more words to read. I wish it could have been a rhyming book because they are more fun to read.I would rate this book 4 out of 5 stars because the pictures are beautifully colored and drawn and the book is easy to read. I would recommend this book to young children who love animals and cool pictures.Highly Recommended: 4 out of 5 starsReviewer: KarmellaMy name is Karmella. I like reading books about Art and my culture. I love to read in the library and share books with my friends. I think reading is important because you learn something new every time you read.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.013 |
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".