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files implementation » time implementation (Expand Search), pilot implementation (Expand Search), assess implementation (Expand Search)
model implementing » model implemented (Expand Search), model implementation (Expand Search), model representing (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
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Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
Published 2025“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”
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Five Operator Lattice Simulation
Published 2025“…</p><p dir="ltr">Running the included file <code>five_operator_lattice_sim.py</code> (Python 3.14 + NumPy 2.1) reproduces the dynamic interactions and figures reported in Appendix A of the paper, generating time-series data that demonstrate operator balance, instability, and renewal cycles.…”
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PTPC-UHT bounce
Published 2025“…<br>It contains the full Python implementation of the PTPC bounce model (<code>PTPC_UHT_bounce.py</code>) and representative outputs used to generate the figures in the paper. …”
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Overview of deep learning terminology.
Published 2024“…Training loops are implemented with the luz package. The geodl package provides utility functions for creating raster masks or labels from vector-based geospatial data and image chips and associated masks from larger files and extents. …”
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Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan)
Published 2025“…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …”
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Compiled Global Dataset on Digital Business Model Research
Published 2025“…</p><p dir="ltr">For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. …”
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Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model
Published 2025“…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”
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Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis
Published 2025“…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”
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