The Search for Treasure: The Sixth Adventure in the Kingdom of Fantasy by G. Stilton, L.M. Tramontozzi, & E. Dami
Bibliographic record
Abstract
Stilton, Geronimo, Lidia M. Tramontozzi, and Elisabetta Dami. The Search for Treasure: The Sixth Adventure in the Kingdom of Fantasy. New York, NY: Scholastic Inc., 2014. Print.In this book, he was in his office working and his friend came to come and get him for a race. They got to the race, a boating race but it was storming. Geronimo had to go to the fairyland to tell the princess a secret. I am almost at the secret and I’ll tell you when I get there. There is nothing I don’t like about Geronimo Stilton books. I think there is looks of detail. And if I could live anywhere it would be in mouse city. I would be a mouse and not a rat. I like when there is lots of BIG LETTERS spelled out, meaning the characters are screaming or hyperbole. I would rate the books as the best book series and give it 5 stars. Highly Recommended: 5 out of 5 starsReviewer: AutumnMy name is Autumn. The books I love most by Geronimo are his adventures and Mystery books. My favorite books by Geronimo Stilton is the search for treasure. I don’t like lots of books so when I read I have to think if I like it or not or if I should put it down but when I see a Geronimo Stilton I read the whole thing. Also like the book the destiny of the phoenix cause it had lots of detail. I like when they go to the fairy land and see all the fairies they have lots of trolls and stuff like that and colors.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.016 |
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".