157 - 2025/04/04 - Drumheller's Dinosaur, Hot Dog Mystery, McBarge, and Peeing on Cars in BC
Bibliographic record
Abstract
In Keep Canada Weird Jordan and Aaron Airport explore the weird and offbeat Canadian news stories from the past week.In this episode your hosts discuss;the death of Drumheller Alberta's last dinosaurVancouver's hot dog mysterythe McBarge McSinksthe salesman who pee'd on a car in BCSeries LinksKeep Canada Weird Series: https://www.nighttimepodcast.com/keep-canada-weirdSend a voice memo: https://www.nighttimepodcast.com/contactJoin the Keep Canada Weird Discussion Group: https://www.facebook.com/groups/keepcanadaweirdProvide feedback and comments on the episode:nighttimepodcast.com/contactSubscribe to the show:nighttimepodcast.com/subscribeContact:Website: https://www.nighttimepodcast.comFacebook: https://www.facebook.com/NightTimePodInstagram: https://www.instagram.com/nighttimepodSupport the show: https://www.patreon.com/nighttimepodcastLearn more about your ad choices. Visit megaphone.fm/adchoices
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.235 | 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".