Bibliographic record
Abstract
Matas, Carol. In My Enemy’s House. Toronto: Scholastic Canada, 2013. Print. The book is about a Jewish Polish girl named Marisa who is trying to survive in World War 2 while over the years losing family members. First her papa then her sisters over time her little brother and mama eventually she travels to Weimar a town in Germany while the only family member she has left is sent off to be a slave she spends a few years in Germany, one year being a Polish slave and being abused and yelled at by her owner until eventually she goes back to Weimar and asks if she can go to a different family. She moves in with a family the father named Herr Reymann and the wife named Frau Reymann with three children named Charlotte, Hans and Monte. She spends a few years there everyone soon treating her like family after a while she moves back to her hometown in hopes of finding any family left. What I liked about the book: very interesting story thrilling suspenseful and overall fantastic. What I didn't like about the book: nothing really except at times it can be kinda violent. I rate the book as a 4.Recommended: 4 out of 5 stars Reviewer: JadisMy name is Jadis. I like horror, fiction, non-fiction I don’t mind they’re all awesome!! Especially Goosebumps. Fantastic stories the thrill is amazing the chills are exciting. I love to read because it gives you a chance to escape into another world. Amazing stories, hilarious adventures all super inspiring.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.238 | 0.148 |
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".