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Record W4412664222 · doi:10.1111/insr.70003

The Role of Dice in the Emergence of the Probability Calculus

2025· article· en· W4412664222 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Statistical Review · 2025
Typearticle
Languageen
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsMcGill UniversityWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsDiceCalculus (dental)MathematicsComputer scienceStatisticsMedicine

Abstract

fetched live from OpenAlex

Summary The early development of the probability calculus was clearly influenced by the roll of dice. However, while dice have been cast since time immemorial, documented calculations on the frequency of various dice throws date back only to the mid‐13th century. This paper examines the conceptual changes that took place between the ancient and medieval worlds regarding dice rolls. Archaeological data and written source material are used to explore various notions around tesseræ, or six‐sided dice, and tali, which are four‐sided dice made from the anklebones of goat or sheep. Given this evidence, it appears that dice rolls provided little or no incentive in Roman society to carry out numerical probability calculations. The first documented frequency computations on dice appeared circa 1260 in the manuscript De vetula , likely written by the English polymath Roger Bacon. In the same period, King Alfonso X of Castile, León and Galicia commissioned a book on games, Libro de los juegos . It is argued that the conceptual changes present in these publications reflect the emerging empiricism, related to dice, and mathematical interests of Bacon and his Islamic predecessors.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.438
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it