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61 to 70 of 140,267 Results
12_DIC.csv
Jun 1, 2026 - Data for: "Constraining environmental controls on the incorporation of Mg, Na and Sr in cultured Globigerina bulloides: implications for biomineralisation and high latitude palaeoceanography"
Comma Separated Values - 132 B - MD5: 6f16fbeedeca72885faae22026a68fbe
HCO3- and CO2 values in µmol/kg for the different experiments.
Mechanical Wave Transmission Measurements in Compressed AlSi10Mg Powder for a Feasibility Study of a Volumetric Metal 3D-Printer
May 31, 2026 - NTNU – Norwegian University of Science and Technology
Teigenes, Oddne Kristoffer, 2026, "Mechanical Wave Transmission Measurements in Compressed AlSi10Mg Powder for a Feasibility Study of a Volumetric Metal 3D-Printer", https://doi.org/10.18710/M5Z2ZO, DataverseNO, V1
This dataset supports the master's thesis "Feasibility Study of a Novel Volumetric Metal 3D-Printer: Researching Attenuation of Mechanical Waves in Aluminum Powder" by Oddne Kristoffer Teigenes, NTNU, 2026. The dataset contains averaged ultrasonic transmission measurements through compressed AlSi10Mg aluminum powder under vacuum and mechanical prel...
00_README.txt
May 31, 2026 - Mechanical Wave Transmission Measurements in Compressed AlSi10Mg Powder for a Feasibility Study of a Volumetric Metal 3D-Printer
Plain Text - 8.7 KB - MD5: bcbf1839f819f0b348bacb9e3e5dc09a
Averages-1.zip
May 31, 2026 - Mechanical Wave Transmission Measurements in Compressed AlSi10Mg Powder for a Feasibility Study of a Volumetric Metal 3D-Printer
ZIP Archive - 26.9 GB - MD5: 74446905d696a29408cd7ef33127759e
Averages.zip contains averaged waveform measurements, derived result files, analysis/acquisition scripts, measurement notes, and supporting risk-assessment documentation for the compressed AlSi10Mg powder transmission experiments.
Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
May 29, 2026 - University of South-Eastern Norway
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, V2
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...
0_ReadMe.txt
May 29, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
Plain Text - 21.2 KB - MD5: d44c4029e684e063091a7b56c176193e
Detailed overview of the repository structure, file contents, workflow steps, reuse guidance, and notes on source traceability. The public release excludes Scopus-derived abstracts and raw Scopus export files.
Codes_Py1_Automated_data_extraction_llm.zip
May 29, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
ZIP Archive - 12.4 MB - MD5: 1c95b307eca112047a61546f8fb2d4b4
Python scripts, configuration files, example inputs/outputs, and documentation for the LLM-assisted extraction of feedstock and technology descriptors from title and abstract fields.
Codes_Py2_Automated_extracted_data_cleaning.zip
May 29, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
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.
Codes_Py3_Automated_validation_llm.zip
May 29, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
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.
Review_DataExtraction_Validation_Curation_FinalDataset.zip
May 29, 2026 - Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
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.
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