Bibliographic record
Abstract
In this paper, we consider the Gergonne m-pile trick and its relation with the base m counting system. The case m = 3 produces one the oldest of mathematical �magic� tricks that involve the reordering of 27 cards. Joseph Diaz Gergonne [3], a French mathematician, was the first to analyze and generalize it in 1813. In [2, pag. 39], Gardner says: Mel Stover, of Winnipeg, Canada, calls my attention to the application of the ternary counting system to the Gergonne pile trick. Immediately, in [2, pag. 40], he also expresses: Reflecting on the above matters led Mr. Stover to the invention of a truly stupendous breath-taking version of the trick. It makes use of the decimal system and a deck of 10 billion playing cards! Based on these cases (m = 3 and m = 10), we demonstrate mathematically the existence of a formal relation between the position of the selected card after applying the Gergonne trick with a deck of mm cards and the base m counting system by using modular arithmetic. Also, we give general mathematical proofs of some particular situations as are: naming the position of the card, bringing the card to a named position and naming the card.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".