Bibliographic record
Abstract
Doman, Mary Kate. Treasure. Costa Mesa: Saddleback, 2013. Print.Treasure, one installment from The Heights series, is the story of Todd Bardo Jr., a junior at Penn State and his adventure diving for treasure off the shore of Ecuador. As a thank you for his work with the poor in that country, Todd’s father, a prominent and respected doctor, was awarded salvage rights to five miles of the reef by the Ecuadorian government. Todd inherits the salvage rights at his father’s death, and needs to complete the dive before his rights expire. With the help of a diving team headed by his best friend’s father, he and his team attempt the impossible – to find and claim treasure from a sunken ship. With her audience in mind, Doman has woven an adventure story driven by plot, dialogue, and simple language. This high-interest low-vocabulary book introduces readers to the country of Ecuador and its colourful history. Through Todd’s eyes we experience the excitement of organizing a treasure dive and some of its challenges. Will Todd find enough money to fund the expedition? Will his ship be targeted by thieves? Will his team be attacked by sharks? Ultimately, will he succeed and find a treasure?Students who appreciate simpler text and an exciting plot will enjoy this read. The resolution of some conflicts seems a bit convenient, but certainly keeps the story moving. The interest level is grade 5 to 8; the reading level is grade 1 to 2. This book is available at Saddleback Educational Publishing.Recommended: 3 out of 4 starsReviewer: Anita HammondAnita Hammond taught English Language Arts and music with Regina Catholic Schools for eleven years. Currently, as a full-time mother, she has returned to Education studies at the University of Alberta in the Masters of Education program specializing in teacher-librarian studies. She has enjoyed the opportunity to read numerous high-interest low-vocabulary titles, and hopes to share these titles and others with colleagues and students to support literacy goals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.323 | 0.264 |
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".