Beauty Worth Sharing: An Introduction to Koinon VI, with Recourse to Marlaina
Bibliographic record
Abstract
Numismatics, especially Classical Numismatics, is chock-full of beautiful surprises worth sharing. Every day I learn something new, and as a community we all relish in what seems to be a daily revelation of novel discoveries. But I’ve come to the conclusion recently that numismatists themselves are just as interesting, in fact even moreso than the coins we all cherish. Fairly recently I met one such numismatist: Her name is Marlaina and it would be a rare occasion to find her without a bag of coins—yes, she keeps them all in a small bag resembling a pencil case, where they are constantly rubbing against each other! Marlaina has been a collector as long as I have (nearly twenty years), and although she mostly collects United States and Canadian coinage, she certainly has a fair share of World coins and even a few ancients. Her favorite numismatic objects, however, are tokens—turnpike tokens, tokens from restaurants, Alcoholics Anonymous tokens, etc. Among these one stands out: a token from McDonalds, which sits in her bag alongside various silver dollars, large cents, and the rest of her treasure. But it isn’t Marlaina’s eclectic collection that makes Marlaina so special, or the fact that she may be the only numismatist that carries the majority of her coins in a bag. The most suprising thing about Marlaina is that she has never seen a coin—Marlaina is completely blind
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".