Commander's Brew - Alesha, Who Smiles at Death - 40
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our 40th show! This week in celebration of our 40th episode we split up brewing Alesha and her hybrid triggered ability with Sean taking Red/White and Andy taking Red/Black. They each discuss the merits and downfalls of two colours verses three and manage to get some sweet decks out of the limitations! Also this week, Massdrop has given us a box of MODERN MASTERS 2015! Pay attention to our twitter @commandersbrew all week to learn how to win a custom deck built by us out of cards we crack from a MM15 box all courtesy of @massdrop! Here's a spoiler: sign up for a Massdrop account and tell us your username! Simple as that! Of course we are still sponsored by our good friends over at Wizard's Tower, so head on over to wizardtower.com for all your Magic needs! Great prices on singles and free shipping on cards within Canada if you spend $15! 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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.183 | 0.023 |
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 it