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2,001 to 2,010 of 2,031 Results
User_manual.pdf
May 16, 2025 - Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
Adobe PDF - 132.2 KB - MD5: 244635960f5adfc3c446e928f4c3cad3
User_manual.pdf
winpython_nlp_2713_CE-SDG_round2_0.py
May 16, 2025 - Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
Python Source Code - 34.1 KB - MD5: 4c88d8345636389baa91f2355e23cbf9
winpython_nlp_2713_CE-SDG_round2_0.py
winpython_nlp_2713_CE-SDG_round2_0.txt
May 16, 2025 - Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
Plain Text - 34.1 KB - MD5: 4c88d8345636389baa91f2355e23cbf9
winpython_nlp_2713_CE-SDG_round2_0.txt
00_ReadMe.txt
Jun 26, 2026 - Stepwise supplement: results of rule-based mappings, validations, and indices (CE–SDG Framework)
Plain Text - 5.3 KB - MD5: 8d4c8100883399b1b18680acaa31df18
CSVs.zip
Jun 26, 2026 - Stepwise supplement: results of rule-based mappings, validations, and indices (CE–SDG Framework)
ZIP Archive - 221.7 KB - MD5: ae9a6baaf424de3271d3081f0396d080
Stepwise supplement results of rule-based mappings, validations, and indices.xlsx
Jun 26, 2026 - Stepwise supplement: results of rule-based mappings, validations, and indices (CE–SDG Framework)
MS Excel Spreadsheet - 539.1 KB - MD5: 89b80a130c4188f1d712249f22e0b7ea
Content_list.pdf
May 16, 2025 - Stepwise supplement: results of rule-based mappings, validations, and indices (CE–SDG Framework)
Adobe PDF - 39.3 KB - MD5: 94d3d8ebbe463b7813ec0be2f4528ac9
Content_list.pdf
Cover.pdf
May 16, 2025 - Stepwise supplement: results of rule-based mappings, validations, and indices (CE–SDG Framework)
Adobe PDF - 31.4 KB - MD5: fab9666ccfe4af7c92d879ed02283148
Cover.pdf
00_ReadMe.txt
Jun 26, 2026 - Supplement to: Leisure Time Patterns of Children with and without Disabilities: A Cross-Sectional Latent Class Analysis
Plain Text - 3.3 KB - MD5: 505f74a431ad7be0bad2eca7d06f2976
01_data_clean-1.R
Jun 26, 2026 - Supplement to: Leisure Time Patterns of Children with and without Disabilities: A Cross-Sectional Latent Class Analysis
R Syntax - 3.2 KB - MD5: d42abb6eea6dba685c8a6cea15187441
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