Missouri S&T Hydrogen Fuel Cell EcoCAR
Bibliographic record
Abstract
Today, the automotive industry is at a crossroads during the worst economic downturn in 75 years.Particularly frustrating is that this crisis struck just at a time when these companies were successfully restructuring themselves and creating a new generation of cleaner, more efficient vehicles.This progress, and the very viability of the U.S.-based auto industry, is threatened.In response to that threat, the U.S. Department of Energy (DOE) and General Motors (GM), as well as by Natural Resources Canada and other industry leaders, established a new collegiate advanced vehicle technology competition (AVTC), the "EcoCAR: The NeXt Challenge."EcoCAR challenges engineering students from universities across North America to re-engineer a light-duty vehicle, minimizing energy consumption, emissions, and greenhouse gases while maintaining the vehicle's utility, safety, and performance.The Missouri S&T was selected in May 2008 as one of only 17 in North America.And in November 2008 Missouri S&T was selected as the only team in U.S.A. to receive hydrogen fuel cells, the cutting-edge powertrain technology for the EcoCAR Challenge.The new Missouri S&T hydrogen testbed used by the EcoCAR project includes the EcoCAR Garage, Hydrogen Fueling Station and the Renewable Energy Transit Depot.The station uses an on-site steam methane reformer and electrolyzer, steel and carbon composite storage tanks, a 350 bar hydrogen dispenser, and a stationary Polymer Electrolyte Membrane (
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".