Alerus Entrepreneurship Challenge 2011
Bibliographic record
Abstract
The Department of Entrepreneurship was proud to host the 2nd Annual Alerus Entrepreneurship Challenge. The Alerus Entrepreneurship Challenge is designed for any undergraduate or graduate student enrolled at a North Dakota or neighboring state college of university. All judges for the competition are experienced entrepreneurs, not faculty, and we are ask our judges to provide useful feedback on every business plan. Cash prizes are awarded to the top three teams, and others prizes will be awarded for the “Best Elevator Pitch” and “Most Innovative Idea.” The competition takes place annually at the University of North Dakota to continue to support innovation, entrepreneurship and development of future business ventures. Students interested in entering the business plan competition need to submit: (1) a one-page abstract (2) an intent to compete form, and (3) a biographical information form. Congratulations to the 2011 Alerus Entrepreneurship Challenge Winners 1st Prize: Adrien Herberts and Peter Yang University of British Columbia Second Prize:Bryce North and Chris Thorne-Tjomsland University of Manitoba Third Prize: Andrew Bentz North Dakota State University Most Innovative: Matthew Schober, Joseph Schlangen, Patrick Hannan University of North Dakota Best Elevator Pitch: Adrien Herberts and Peter Yang University of British Columbia Stay tuned for information on the 2012 challenge coming soon!
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.052 | 0.038 |
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".