Reproducibility package for: Constructive Parameter Fibers and Minimal Outputs for Mammillary Compartment Models

Reproducibility package for the paper “Constructive Parameter Fibers and Minimal Outputs for Mammillary Compartment Models” (Guiying Lyu, Hongyu Cao, Ahmad Yahya Dawod). This archive contains all Python/Anaconda source code, exact computational certificates, generated data, and figures that support the manuscript. No empirical or patient data are included. The computations serve as reproducibility and falsification checks; the mathematical proofs in the paper are independent of the code. The package verifies: • closed-form input–output polynomials; • explicit one-output rational parameter fibers; • multi-output constructive inverse maps and permutation ambiguity; • predicted finite-field Jacobian ranks; • exact small-n (n = 4,5,6) forward/reverse fiber coverage and collision limits; • the six-compartment in-silico tracer example (liver, kidney, muscle, adipose) together with its two figures. A total of 241 algebraic and Jacobian-rank checks are reported in the manuscript; three additional exact statements support the biological illustration. All algebraic checks use exact rational arithmetic or finite fields. Floating-point arithmetic is used only for trajectory visualization. How to reproduce: conda env create -f environment.yml conda activate jca-mammillary python run_certificate.py Alternatively: python -m venv .venv python -m pip install -r requirements.txt python run_certificate.py Successful completion is indicated by “all_checks_passed”: true in output/data/computational_certificate.json. The full suite normally finishes in a few seconds on a standard CPU and requires no proprietary computer-algebra system, GPU, network access, or external data. Licenses: source code under MIT; data, certificates, figures and documentation under CC BY 4.0.论文《乳突型房室模型（Mammillary Compartment Models）的构造性参数纤维（Parameter Fibers）与最小输出》（Guiying Lyu、Hongyu Cao、Ahmad Yahya Dawod 合著）的可复现性套件。 本归档文件包含支撑该论文的全部Python/Anaconda源代码、精确计算验证证书、生成数据集与插图。本套件未包含任何实验或患者相关数据。本计算工作仅用于可复现性验证与证伪检验；论文中的数学证明与本代码无依赖关系。 本套件可验证以下内容： • 闭合形式输入输出多项式 • 显式单输出有理参数纤维（rational parameter fibers） • 多输出构造性逆映射与置换歧义性 • 预测有限域（finite-field）雅可比矩阵秩（Jacobian ranks） • 精确小阶（n=4、5、6）正向/反向纤维覆盖度与碰撞限 • 六室硅基（in-silico）示踪剂示例（涵盖肝脏、肾脏、肌肉、脂肪组织）及其配套的两幅插图 论文中共报告了241项代数与雅可比矩阵秩验证任务；另有3项额外精确结论支撑该生物学示例。所有代数验证均采用精确有理算术或有限域运算，浮点运算仅用于轨迹可视化。 复现步骤如下： conda env create -f environment.yml conda activate jca-mammillary python run_certificate.py 或采用以下方式： python -m venv .venv python -m pip install -r requirements.txt python run_certificate.py 当output/data/computational_certificate.json文件中出现"all_checks_passed": true时，表示验证全部通过。在标准CPU环境下，整套验证流程通常可在数秒内完成，且无需专有计算机代数系统、GPU、网络访问或外部数据。 授权协议：源代码采用MIT协议；数据集、验证证书、插图与文档采用CC BY 4.0协议。