Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Three students from Central Washington University have come together to design and manufacture a unique RC Car for the annual regional RC Baja Car competition held by the American Society of Mechanical Engineers (ASME). The RC car will compete in three events, Baja, Slalom and Sprint. The objective for this project was to create a unique build based off previous team’s projects. The new design was optimized for functionality and performance to compete in each event and excel above other competition as well. The design process before finalizing on a design that resembled that of a real car was thoroughly calculated and researched. The new chassis was created from wood rather than metal which allowed for a custom design and significant amount of weight reduction from more than 7 pounds down to an impressive 5 pounds. Using manufacturing machines such as drill presses, routers, table saws, and mills, connection locations on the chassis for each component was created. To simulate jumps and crashes, the car was subjected to a 2-foot drop and frontal impact. The results showed the vehicle could withstand the 2-foot drop without compromising performance. The frontal impact test resulted in minimal damage that did not compromise the operation of the vehicle.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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 it