Classic Children's Books Collection 0
Bibliographic record
Abstract
Dive into this joyous collection of classical children’s books from some of the best writers for little hearts and young minds.Uncover the magic of childhood classics from ´Anne of Green Gables´, ´The Wind in the Willows´, and ´The Secret Garden´ to ´The Velveteen Rabbit´ and ´The Wonderful Adventures of Nils´.Follow one girl's search for belonging, go on thrilling adventures with our favourite furry friends, discover a magical garden, learn about love and reality with a toy rabbit, and join one boy as he embarks on fantastical farmland adventures!Weaving a touching and intoxicating collection of coming-of-age tales, this ‘Classic Children's Books Collection’ is the perfect companion for fans of Netflix’s ‘Anne with an E’.Lucy Maud Montgomery (1874-1942) was a Canadian author and poet. Best known for her novel ‘Anne of Green Gables’, it remains one of the best-selling books worldwide and has been adapted for both stage and screen.Kenneth Grahame (1859-1932) was a British writer born in Edinburgh, Scotland. He is most famous for the children’s classics ‘The Wind in the Willows’ and ‘The Reluctant Dragon’.Frances Hodgson Burnett (1849-1924) was a British-American novelist and playwright. Best known for her celebrated children’s novels, Burnett’s work spans ‘Little Lord Fauntleroy’, ‘A Little Princess’, and ‘The Secret Garden’.Selma Lagerlöf (1858-1940) was a Swedish author and the first woman to win the Nobel Prize in Literature. Her work spans ‘The Saga of Goesta Berling’, ‘The Wonderful Adventures of Nils Holgersson’, and ‘Jerusalem’.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.578 | 0.367 |
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".