Blue Jays need win over Royals in game 3 of AL playoffs
Bibliographic record
Abstract
Down two games to none is nothing new for the Toronto Blue Jays as they host the Kansas City Royals in game 3 of the American League Championship Series on Monday night. The Blue Jays were in that same boat against the Texas Rangers in the Division Series and came back to win it. But the Royals are a better team than the Rangers. Toronto looked like they were going to even the series leading 3-0 in Game 2, only to see the Royals rally for 5 late runs to win 6-3. KC's Ben Zobrist says it's great to be up 2-0, but it really doesn't change anything for the them cut (Zobrist) History is on the Royals side though. The team that's won Game 2 of this series over the last 29 years has made it to the World Series 23 times, including 14 of the last 16 years. Kansas City starts Johnny Cueto, who's finally beginning to look like the pitcher they thought he'd be when they got him from Cincinnati at the trade deadline. Toronto counters with Marcus Stroman, who'll be making only his 5th start with the team. I'm Jack Schmerer and you're listening to Rivet.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.001 |
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".