Tools for Tomorrow's Science and Technology Workforce: MATE's 2006 ROV Competition Sets Students' Sights on Ocean Observing Systems
Bibliographic record
Abstract
Teams participating in the 2006 ROV competition organized by the Marine Advanced Technology Education (MATE) Center and the Marine Technology Society's (MTS) ROV Committee experienced first-hand the scientific and technical challenges that many ocean scientists, technicians, and engineers face every day. The competition tasked more than 1,000 middle and high school, college, and university students from Newfoundland to Hong Kong with designing and building ROVs to support the next generation of ocean observing systems. Teaming up with the National Office for Integrated and Sustained Ocean Observations, Ocean.US, and the Ocean Research Interactive Observatory Networks (ORION) Program, the competition highlighted ocean observing systems and the careers, organizations, and technologies associated with ocean observatories. The student teams were challenged to develop vehicles that can deploy, install, and maintain networks of instruments as well as to explore the practical applications and the research questions made possible by observing systems
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.060 | 0.025 |
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".