Bibliographic record
Abstract
DeLand, M. Maitland. The Great Katie Kate Explains Epilepsy. Austin, TX: Greenleaf Books, 2014. Print.The Great Katie Kate Explains Epilepsy marks the fourth book in this educational series written by M. Maitland DeLand. As a radiation oncologist who specializes in the treatment of children, Dr. DeLand began this series as a way of helping children and their caregivers learn about the child’s particular condition. Each book in the series recounts a story of a child learning about their illness from the Great Katie Kate, a young, readheaded superhero who swoops in to answer their questions and help them combat the “Worry Wombat,” a furry manifestation of the child’s anxieties that only goes away once their questions are answered.Based on the premise that kids are sharp and that information can help them, this book provides concise and clear information about epilepsy. It documents the experiences of Jimmy, a young boy who has seizures and is taken to hospital. There, he encounters the Great Katie Kate, who takes Jimmy and several other young people on a journey where she and the other children explain epilepsy, its diagnosis, and its treatment.Overall, the book provides clear explanations of the types, diagnosis, treatment, and management of epilepsy. Any complex terms in the book are the actual medical names bound to be used by their treatment teams. Although the text may be too long or complicated for a very young child to read on their own it is of an acceptable level for 8-12 age range. The illustrations are colourful and generally informative.Recommended: 3 out of 4 stars Reviewer: Robin DesmeulesRobin is an Academic Librarian Intern at the J.W. Scott Health Sciences Library at the University of Alberta. Robin is an avid devourer of fiction of all kinds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.134 | 0.073 |
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".