Bibliographic record
Abstract
Greetings everyone! This issue of Deakin news focuses primarily on several events happening across Canada, including a few shortlist announcements. Awards Finalists for Newfoundland and Labrador Book AwardsFor a list of finalists read more at the Canadian Children’s Book Centre Website VCRL 2018 Information Book Award Shortlist Announced For a list of the 10 titles on the shortlist, see the VCRL website.Roundtables voting deadline: October 31, 2018Winner announcement: November 2018 Events Telling Tales FestivalWestfield Heritage Village, Rockton OntarioSunday September 16, 2018 The Children’s Book Bank Presents An Evening with Emma DonoghueThursday, September 20, starting at 6:00 pm at Daniels Spectrum 585 Dundas Street East in Toronto, Ontario Word on the Street TorontoHarbourfront CentreSunday September 23, 2018 (includes a “kids zone” area) WordFest - Calgary, ABOctober 8-15, 2018Memorial Park LibarySee the Youth Program for details The Annual VCLR Illustrator’s Breakfast: How do they do that?October 13, 2018 | University Golf Course | Vancouver BC Breakfast & presentations: 8:00 am - 12:00 pmWorkshop: 12:30 – 1:30 pmEarly Bird Rates end September 23, 2018 Book Bash: Canadian Children's Literature FestivalSaturday, October 20 from 12:00 - 4:00 p.mHarbourfront Centre To conclude, I leave you with this quirky list of books from The New York Times entitled “Charming, Plucky Picture Books That Ease Back-to-Class Jitters.” All the best for an enjoyable fall and happy reading! Hanne Pearce
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.492 | 0.446 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".