Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reviewed by: Bike Thief by Rita Feutl Elizabeth Bush Feutl, Rita. Bike Thief. Orca, 2014. [136p] (Orca Soundings). ISBN 978-1-4598-0570-5 $16.95 ISBN 978-1-4598-0569-9 $9.95 ISBN 978-1-4598-0572-9 $9.95 Reviewed from galleys R Gr. 7-9. Katie’s innate clumsiness has resulted in some domestic damage, and her brother, narrator Nick, is afraid that their foster parents—one of the rare families willing to take on a pair of siblings—will ask for the siblings’ reassignment. Therefore, Nick makes a quick deal with a shady dealer, Dwayne, to replace a broken TV, on the condition that Nick pays him back in service. The favor, it turns out, is to recruit and direct “runts,” underage kids with no criminal record, to steal high-end bicycles and help rebuild them at the chop shop Dwayne supervises. Naïve and desperate, Nick complies, using his love of fixed-up bikes to spot prime merchandise. It quickly becomes evident, though, that the chop shop is merely a front for a serious drug ring, and when another recruiter like Nick is beaten and kidnapped, Nick must decide whether to expose his own crimes to save the boy’s life. The compressed time frame of the episode fits well into the Orca Soundings hi-lo format, and the plot boasts notable authenticity in taking inspiration from a real-life Edmonton workspace that, according to the acknowledgments, helps kids “build and maintain their own bikes.” Details of the thieves’ m.o. are less likely to serve as instructions in larceny than as a warning to protect your own property from crimes of opportunity. This title will serve not only the hi-lo crowd but any YA reader looking for a lightning-paced super-quick pick. [End Page 516] Copyright © 2014 The Board of Trustees of the University of Illinois
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it