MétaCan
Menu
Back to cohort
Record W4412544362 · doi:10.1007/978-3-031-98685-7_20

PyEuclid: A Versatile Formal Plane Geometry System in Python

2025· book-chapter· en· W4412544362 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

VenueLecture notes in computer science · 2025
Typebook-chapter
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsPython (programming language)Computer scienceProgramming languageGeometryComputer graphics (images)Engineering drawingMathematicsEngineering

Abstract

fetched live from OpenAlex

Abstract We introduce , a unified and versatile Python-based formal system for representing and reasoning about plane geometry problems. designs a new formal language that faithfully encodes geometric information, including diagrams, and integrates two complementary components to perform geometric reasoning: (1) a deductive database with an extensive set of inference rules for geometric properties, and (2) an algebraic system for solving diverse equations involving geometric quantities. By seamlessly combining these components, enables human-like reasoning and supports generating concise reasoning steps (proofs), either fully automatically or through interactive guidance. Benchmark evaluations demonstrate that outperforms existing tools, solving a broader range of problems across both proof generation and calculation tasks. Moreover, holds significant potential for educational use and integration with advanced deep learning systems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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