Algebrica is a free, ad-free, university-level mathematics knowledge base. This repository hosts the source content of the entries published on the site, released progressively in Markdown format and reusable under a non-commercial license.The repository progressively includes:
- the original source files of the entries written for Algebrica in Markdown and LaTeX format;
- fully editable SVG illustrations, including both vector structures and text elements, which can be modified directly through the source code;
- a semantic JSON layer containing definitions, properties, lemmas, theorems, and other formal mathematical structures associated with the entries, designed to be portable, reusable, and openly accessible;
- Markdown-based flowcharts describing the main logical and procedural steps behind common mathematical processes and problem-solving methods.
Each entry on Algebrica is written from scratch, drawing on a broad range of sources: university textbooks, lecture notes, and reference works in mathematics. The selection, structure, and presentation of the material are shaped by an engineering background.
Where sources differ in notation or emphasis, they are compared and reconciled, then reorganised into a single coherent flow that follows a deliberate, logical progression. The resulting content is original: each entry is an independent exposition, built from the ground up to be accurate while remaining clear for the intended reader.
The editorial aim is to reduce without distorting. University sources are often dense by necessity, and part of the work is finding what can be made more direct without losing precision.
The process is iterative. A page that seems complete may be revisited as adjacent entries develop, and inconsistencies in notation, terminology, or depth often prompt further revision. Entries are progressively released and updated here on GitHub.
To increase transparency, I am also documenting the editorial process and continuously revising the content to improve accuracy and reliability. Since I am not a native English speaker, I also rely on Grammarly Pro (no affiliation) to support the proofreading of the texts. On some pages a quality indicator is now visible, including a GPTZero Pro score (no affiliation), as an additional signal of transparency. The score, expressed as a percentage, represents the system’s level of confidence that the content is human. For example, a score of 92% means that the text is considered human with 92% confidence.
This should however be interpreted with caution.
The inclusion of these indicators is primarily an effort toward transparency, but the results are often inconsistent and sometimes contradictory. In particular, formal mathematical definitions and the writing style of a non-native English speaker can significantly affect the score. In several cases, extremely small lexical changes have produced large variations in the reported confidence. For example, replacing a simple conjunction such as "whether" with a synonym has in some tests shifted the score from 18% human to 72% human, even in texts with an extended and coherent contextual structure.
Such variations suggest that these systems may not yet provide a stable or fully reliable measure of authorship. I am also testing other similar tools, but the results remain highly variable and, at least for now, only partially indicative.
Any help in making the texts sound more natural in English, while preserving the formal accuracy they would have in Italian, is absolutely welcome!
In the Algebrica GitHub repository I’m progressively releasing not only all the entries in Markdown format, but also all the diagrams and illustrations as open and fully editable SVG files to improve the accessibility and reusability of the content.
The SVG images can be freely modified, reused, and adapted for educational purposes, making the graphical structure of the entries fully inspectable and portable alongside the text itself.
Content is released under Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0). It can be reused for non-commercial purposes, with attribution.
- Website: algebrica.org
- X: @antoniolupetti