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: Gum by Nancy Willard Elizabeth Bush Willard, Nancy Gum; illus. by Jeff Newman. Candlewick, 2017 [32p] ISBN 978-0-7636-7774-9 $14.99 Reviewed from galleys R 4-7 yrs James rustles his sleeping parents up at six in the morning to collect his week’s allowance—five quarters, one of which is a Canadian coin that his bleary-eyed mother assures him is lucky. “Lucky, ” as in now-please-go-away. After school he and pal Danny head to Mr. Wright’s store, where they take turns inserting their entire net worth into a gumball machine in the hope of getting the little silver racer that never wants to drop down the chute. Each quarter earns six gumballs, or at best a cheesy ring or, surprisingly, a little wheel. (“‘But this machine doesn’t give wheels, ’ says James. ‘It does now, ’ says Danny.”) James is resolved to save his last lucky quarter, but when he tests the Canadian coin against the slot size, it accidentally drops in and everything in the machine flies out—except the racer. After apologies and clean-up, James is now out his money, has no racer, and doesn’t even like gumballs. Mr. Wright is feeling generous, though, and after he takes off the machine’s top, the three-wheeled racer emerges, and Danny is pleased to share his prize wheel. It isn’t much of a story—for many it’s just a trip down their own boulevard of broken dreams—but Willard is an ace at drawing out the tension as each ensuing coin buys inevitable disappointment. Newman’s ultra-streamlined compositions are a hoot, particularly the early morning bedroom scene, and peppy hues (the color of artificial food additives . . . yum!) are ensconced between Bazooka-pink endpapers. It’s never too early to start playing the slots. Copyright © 2017 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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