Trump COVID, National Depression Screening Day, Dr. J, K-9 calendar
Bibliographic record
Abstract
Welcome to The Morning News Podcast for Monday, October 5th.We begin with the latest from Washington - and President Donald Trump's COVID-19 diagnosis. We get the details on the President's weekend appearance outside the Walter Reed medical centre from Reggie Cecchini - Global's Washington Correspondent.Next we look at a free online screening tool for depression being offered up by the Calgary Counselling Centre. We hear about the resources in our city to battle depression - which has been on the rise during the Pandemic.Continuing our conversation on depression - we speak with Dr. Ted Jablonski - our 'on-call' family physician - about a new study which looks at the negative impact Social Media can have on individuals who rely too much on the APPS and websites for information on COVID-19.And finally - it's that time of the year again....We get the details on this year's K-9 calendar in support of the Calgary Police Youth Foundation. We'll also hear about a milestone for the K-9 unit - which has been operating in our city now for 60 years.
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 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) | 0.263 | 0.003 |
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".