Bibliographic record
Abstract
NOVA. ‘Can This Dinosaur Glide?’ PBS.org, http://www.pbs.org/wgbh/nova/nature/can-dinosaur-glide.html. Accessed 15 February 2017. In 2008 NOVA, the long-running science series produced by PBS, created an interactive wind tunnel test to explore the glide capabilities of the Microraptor, a small feathered dinosaur discovered in China in 2000. The premise for the test is certainly intriguing for both children and adults: site visitors are invited to take the dinosaur for ‘a spin in this virtual wind tunnel’ (NOVA, ‘Can This Dinosaur Glide?’). However, the actual interactivity is less exciting than suggested. Instead of trying to keep a Microraptor aloft in a wind tunnel, the visitor is directed to position the legs and angles of attack to try to optimise Microraptor’s glide path, and subsequently provided with feedback regarding each position’s effectiveness. While some users still may find this interesting and educational, NOVA spoils the discovery aspect of the activity by stating the optimum angle of attack before you even begin.The organisation of the activity is straightforward. There are only a few areas to explore so there is no confusion when navigating, and information appears in textboxes after selecting the appropriate command. Furthermore, the graphics are generally effective, and the colour scheme allows the site to be readable - a benefit, considering the amount of text. The Wind Tunnel Test has enough user engagement to qualify as interactive but it is very limited and rather uninspiring. Where it fails the most, however, is in the lack of enhancements. There is no video or audio, or even advanced graphics, to engage the user on multiple levels. NOVA has included a transcript from the original scientific tests on which this activity is based, but I feel it would not be very absorbing for children to read. The premise of the activity is intriguing, and some older children might be interested enough in dinosaurs and physics to see past the basicness of the activity to the fascinating scientific discoveries it represents. I feel that younger children, however, will be bored and lose interest by its reliance on text, rather than action.Recommended with reservations: 2 out of 4 starsReviewer: Elizabeth Linville Elizabeth is a graduate student in the School of Library and Information Studies at the University of Alberta. When she was a child, she thought dinosaurs were terrifying until it was discovered they had feathers.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.282 | 0.238 |
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".