Bibliographic record
Abstract
Hello! As this issue quickly follows our last there are only a few news items to share with you. The Forest of Reading / Festival of Trees 2019 which is a national festival, held its largest event in Toronto from May 14 to 16. Students read a variety of Canadian children’s books throughout the year and then vote on their favourite book. Awards are then granted for books in a variety of different categories. The Canadian Children’s Book Centre has a lovely summary article about the festival that includes a lengthy list of all the winners. You can also see all the nominees for the various awards on the Ontario Library Association website. The Vancouver Children's Literature Roundtable (VCLR) has announced it’s Information Book Award Shortlist. It includes eight juvenile non-fiction titles. Voting for winners continues into the fall and the winner will be announced in November. The Canadian Children’s Book Centre’s Annual General Meeting will be taking place on Wednesday, June 5, 2019 at 6:00 pm. CCBC members and the general public are welcome to attend: Room 224, Northern District Library / 40 Orchard View Blvd. / Toronto, Ontario M4R 1B9 On a final note, the Children’s book author Judith Kerr passed away earlier this month. Kerr was known for her book The Tiger that Came to Tea. The New York Times recently published an obituary tribute to Kerr. Best wishes for a wonderful summer! Hanne
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.832 | 0.815 |
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".