Bibliographic record
Abstract
Spam! Not the pressed meat, but the act of repeating something a bunch of times! Sean and Andy each picked a non-legendary creature and focus the deck around getting it to hit the battlefield as many times as possible! Sean went with the Gray Merchant, and Andy spams Mulldrifter ! Check out the video version of this podcast at https://youtu.be/jYhtRrOmOag We now have a Patreon page! Go to www.patreon.com/commandersbrew if you'd like to donate and get all the cool perks! Head on over to wizardtower.com for all your Magic needs in Canada AND the USA! Great prices on singles and free shipping on cards within Canada and the US if you spend $15 or $10 respectively! Plus if you use our coupon code, towerofbrews, you'll get 5% off any order over $15! We have our own website now! Visit www.commandersbrew.com for direct downloads and a streaming version of the podcast. Check out the decks we've brewed on tappedout.net: http://tappedout.net/users/commandersbrew Follow us on twitter at @commandersbrew and individually we are @seantabares and @andyhullbone.
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) | 0.750 | 0.025 |
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".