084 How to Make Your Own Cheese with David Asher
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
Want to learn how to make delicious cheeses in your own kitchen? It’s easier than you think. Our guest this week is radical natural cheesemaker David Asher, author of The Art of Natural Cheesemaking: Using Traditional, Non-Industrial Methods and Raw Ingredients to Make the World’s Best Cheeses . During the podcast we discuss: The difference between natural cheesmaking and the way most cheese is made in North America. Using a kefir culture to make cheese. The importance of quality milk. What if I can’t get raw milk? Easy cheeses. The ins and out of rennet and how to make your own. WalcoRen rennet . Using cardoon flowers instead of rennet. Tools you need for cheesemaking. Hacking a fridge to make your own cheese cave. Using leftover whey for fertilizer and cooking. Making chèvre. How to store cheese. The cheese scene in Canada and the legality of raw milk. Raw milk cheeses in Quebec. To find out about David’s classes visit his website The Black Sheep School of Cheesemaking .
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) | 0.000 | 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) | 0.080 | 0.010 |
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