Bibliographic record
Abstract
Green, John. The Fault in Our Stars. New York: Penguin Books, 2014. Print.[Spoiler Alert!]The name of my book is The Fault In Our Stars. The author is John Green and the publisher is the Penguin Group in 2014. My book is about a girl named Hazel Grace and she is sixteen years old. Hazel has cancer in her lungs and she meets a boy in her support group his name is Augustus Waters. Augustus had cancer but he got his cancer taken away from taking his leg but later on he gets cancer again! Augustus and Hazel fall in love but they don’t get to spend a lot of time together because Augustus's cancer makes him die!I liked that at some points in the book when it’s getting to sad it will get really funny! Or when the book seems real in my mind! I like that the book takes me to a whole new worldI didn’t like that Augustus dies right when things in life where getting good for them! I did not like that when Hazel goes to the place she dreamed going and to meet the guy who was there to tell her what it was about was a disappointment because the guy was mean and didn’t want to help her!My rating for the book would be four out of five.I would recommend this book to kids that are older than me because there are lots of hard words and some material that is hard to understand!Highly Recommended: 4 out of 5 starsReviewer: KiaraMy name is name Kiara and my favorite books to read are mystery and horror. My favorite book to read is miss peregrine's home for peculiar children because it is a bit of a mystery and a little bit of horror in the book. I think that reading is important because it helps you understand and read things!
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.037 |
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".