Tesla, Auto Tariffs, and Trump + Date Rape Drug Detection
Bibliographic record
Abstract
On this week's show, Amber and Jeff chat about Trump's new automotive tariffs with APMA's Flavio Volpe and why Tesla might be the only winner. On TheOther Mac, Jeff dives into everything you need to know about Signal-gate and what went wrong when US officials decided that was a good place for planning an attack. We also share some incredible news about a stir stick that can detect date rape drugs, unpack AI election ads on social media, and discuss the latest development in transparent solar cells, online research, and lots more.Check out our guests on social...Flavio Volpe, President of Automotive Parts Manufacturing Association of Canada: X/Twitter | LinkedInErin Kelly, CEO of AskPolly.ai: X/Twitter | LinkedInAddy Graves, Co-Founder & CEO of Cashew Research: LinkedInAnd be sure to follow our hosts...Amber Mac: Bluesky | X/TwitterJeff MacArthur: Bluesky | X/Twitter
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".