Defencemen highlight 2015 Hockey Hall of Fame class
Bibliographic record
Abstract
A trio of defencemen will take center stage when they are inducted into the Hockey Hall of Fame this year. Former Detroit Red Wings Niklas Lidstrom is one of the three. He spent 17 years with the Wings, winning 7 Norris Trophies for best defender and 4 Stanley Cups. Joining him will be a former teammate, forward Sergei Fedorov. In 1,248 career games, Fedorov scored just shy of 500 goals and was the first Russian-born player to win the Hart Trophy- the MVP award- in 1994. Also in class of 2015, defenceman Chris Pronger...who isn't even retired...and was actually just traded over the weekend. He hasn't played because of concussion issues since the 2011-2012 season and isn't expected to play again. Pronger won the Hart Trophy in 2000, won 2 Olympic gold medals, and was named an All-Star four times. Legendary blueliner Phil Housley waited 9 years before getting the call to the Hall of Fame...he's the 4th highest-scoring defenceman in NHL history, and played in nearly 1,500 career games with 8 different teams. Joining the men is one of the most decorated WOMEN'S hockey players in history...American Angela Ruggiero. She won 4 olympic medals, including the gold in 1998. She's just the 4th woman elected to the Hockey Hall of Fame as a player. The 2015 Induction Celebration will be held on Monday, November 9th at the Hockey Hall of Fame in Toronto.
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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 | 0.001 | 0.002 |
| 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 | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.681 | 0.362 |
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".