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151 to 160 of 2,102 Results
Exercise_Developing-New-Ideas.mp3
Jan 21, 2026 - Supporting Data for: Innovation through Intuition
MP3 Audio - 43.5 MB - MD5: e984fb7c0d6dd2ed01dffa8d098e0770
Exercise_Facing-Unexpected-Challenges.mp3
Jan 21, 2026 - Supporting Data for: Innovation through Intuition
MP3 Audio - 38.0 MB - MD5: 1a1683906843151a8215bdfd2890181c
Exercise_Finding-Vital-Resources.mp3
Jan 21, 2026 - Supporting Data for: Innovation through Intuition
MP3 Audio - 39.6 MB - MD5: 5acba267a546fc7061c4f669ca365f94
Exercise_Gaining-Fresh-Perspectives.mp3
Jan 21, 2026 - Supporting Data for: Innovation through Intuition
MP3 Audio - 39.5 MB - MD5: ce35790aa2af782a06022e550ca7c744
Exercise_Taking-Next-Steps.mp3
Jan 21, 2026 - Supporting Data for: Innovation through Intuition
MP3 Audio - 34.1 MB - MD5: daf2b045fa3dcf5a470e4ebd0761e95b
Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
Jan 16, 2026
Barahmand, Zahir, 2026, "Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies", https://doi.org/10.18710/JM6U7B, DataverseNO, V1
This dataset was developed to systematically characterise feedstock–technology relationships across eight major biomass conversion technologies by mining a large Scopus-derived bibliographic corpus (1887–2025; partial coverage for 2025). The workflow is LLM-assisted and fully reproducible, combining automated extraction of feedstock and technology...
Codes_Py1_Automated_data_extraction_llm.zip
Jan 16, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
ZIP Archive - 107.5 MB - MD5: 2792a734810fc784da1561dfbf60ff18
Codes_Py2_Automated_extracted_data_cleaning.zip
Jan 16, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
ZIP Archive - 109.3 MB - MD5: 3796e6f20448f0c25e0096af309c4bcb
Codes_Py3_Automated_validation_llm.zip
Jan 16, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
ZIP Archive - 116.9 MB - MD5: 2d94fe604f5c14f2265b88ca2c58787a
ReadMe.txt
Jan 16, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
Plain Text - 20.7 KB - MD5: a40d689a35fc845eb8c6ab7558622d0f
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