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ZIP Archive - 14.6 MB - MD5: b2b0300a1411ec244409217c1d6f0f12
Python scripts and documentation for rule-based cleaning, heuristic scoring, and validation-status assignment of the extracted feedstock and technology descriptors.
ZIP Archive - 30.9 MB - MD5: 7f096b9d59fcae9952608d30ecd882dc
Python scripts and documentation for targeted LLM-assisted validation of uncertain or non-accepted records after rule-based cleaning.
ZIP Archive - 138.6 MB - MD5: fab016b2ffd7b55a91de062f0abca390
Processed and derived datasets from the extraction, cleaning, validation, and manual-curation workflow, including bibliographic source identifiers, intermediate outputs, and the final curated feedstock–technology descriptors. Scopus-derived abstracts and raw Scopus exports are not included.
May 28, 2026 - University of Bergen
Skare, Mats, 2026, "Clangorous Beasts Data", https://doi.org/10.18710/KPOIWF, DataverseNO, V1
Geolocational and artifactual data from the thesis "Clangorous Beasts - Unraveling the source value and symbolism of metal-detected artifacts with animal representations from AD 550–750/800 found in west and east Norway"
May 28, 2026 - Clangorous Beasts Data
Plain Text - 6.1 KB - MD5: 992090f2fd605f4128689e495b58fb98
May 28, 2026 - Clangorous Beasts Data
application/msaccess - 1.2 MB - MD5: 96fb816619411fb9268f95763851bdf5
May 28, 2026 - Clangorous Beasts Data
Plain Text - 152.8 KB - MD5: 9d493700316c7715095da4f3aae5bf76
May 27, 2026 - Norwegian Institute of Bioeconomy Research (NIBIO)
Heggem, Eva Solbjørg Flo, 2026, "Replication Data for: Agroclimatic zones for Norway", https://doi.org/10.18710/XGMHGE, DataverseNO, V1
Agroclimatic zones of Norway – classification of agricultural land based on crop models and subsidy claim data. Authors: Dorothée Kolberg , Eva S. F. Heggem, Anne K. B. Olsen, Mats Höglind, Hugh Riley and Sigridur Dalmannsdottir. In Norway agroclimatic zones (ACZs) are a valuable tool for national analyses in subject areas concerning optimized mana...
Comma Separated Values - 137.7 MB - MD5: 5e6ee6cf5612d04c26fd704d083a4241
Plain Text - 4.2 KB - MD5: 7d4861139ed2c743f4ba78ce8463b4f6
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