Interview with Timmy Stützle (Pt.2)
Bibliographic record
Abstract
Ross Levitan and Brandon Piller are joined for Part 2 of their interview with Ottawa Senators 3rd overall pick in the 2020 NHL Draft, Timmy Stützle. He discusses what he's focussed on improving, whether he would he prefer to play in Mannheim or Belleville, what he knows about the City of Ottawa, which German players he looked up to and more! Ross and Brandon also debate who Tim should play with on his line to start his career in the NHL....and in Belleville. Follow us on Twitter: @SensCentralSupport us by supporting our sponsors!!! BuiltGo: Visit BuiltGO.com and use promo code \\"LOCKED,\\" and you'll get 30% off your next order. Use promo code \\"LOCKED\\" for 30% off at builtGO.com LET'S GO! Learn more about your ad choices. Visit podcastchoices.com/adchoices
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.718 | 0.013 |
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; both teacher heads agree on what is shown here.
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".