The Mayor, AB's ICU System, US Election Updates, 111 Places In Calgary and Flashback 80's
Bibliographic record
Abstract
Welcome to The Morning News Podcast for Friday, November 13th.We begin with our weekly conversation with Mayor Naheed Nenshi. We get the Mayor's thoughts on the new restrictions announced yesterday by the Province in an attempt to 'flatten the curve'.Could the rising COVID-19 cases in Alberta cause a 'collapse' in Alberta's ICU system? We speak with a University of Alberta Professor, and former Intensive Care Physician who has concerns.Next we look at the ongoing 'saga' of the US Election. We talk about the steps ahead for President Elect Joe Biden, as Donald Trump still refuses to concede. We're joined by Jennifer Johnson, Global News Washington Correspondent.Then we flip through the pages of a new read focused on the many 'hidden gems' our city has to offer. We speak to the author of \\"111 places in Calgary that you must not miss\\".And finally, it's TOTALLY AWESOME! We take a trip back in time - with our weekly \\"Flashback Friday\\" series. Buckle up....this week we travel to the land of big hair, fluorescent clothing and music videos - the 1980's!
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".