Predictive modeling of post‐blast <scp>TNT</scp> residue recovery using semi‐quantitative <scp>LC</scp> – <scp>MS</scp> / <scp>MS</scp> data and machine learning
- DOI
- 10.1111/1556-4029.70511
- Published
- 2026-11-05
- Container
- Journal of Forensic Sciences
- Publisher
- Wiley
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1111/1556-4029.70511,
title = {Predictive modeling of post‐blast
<scp>TNT</scp>
residue recovery using semi‐quantitative
<scp>LC</scp>
–
<scp>MS</scp>
/
<scp>MS</scp>
data and machine learning},
author = {Neslihan Kulahlioglu and Osman Tuysuz and Elif Sude Memis and Yucel Cimtay and Ismail Ethem Goren and Nebile Daglioglu},
year = {2026},
journal = {Journal of Forensic Sciences},
doi = {10.1111/1556-4029.70511},
url = {https://doi.org/10.1111/1556-4029.70511}
}RIS
TY - JOUR
TI - Predictive modeling of post‐blast
<scp>TNT</scp>
residue recovery using semi‐quantitative
<scp>LC</scp>
–
<scp>MS</scp>
/
<scp>MS</scp>
data and machine learning
AU - Neslihan Kulahlioglu
AU - Osman Tuysuz
AU - Elif Sude Memis
AU - Yucel Cimtay
AU - Ismail Ethem Goren
AU - Nebile Daglioglu
PY - 2026
JO - Journal of Forensic Sciences
DO - 10.1111/1556-4029.70511
UR - https://doi.org/10.1111/1556-4029.70511
ER - APA
Kulahlioglu, N., Tuysuz, O., Memis, E. S., Cimtay, Y., Goren, I. E., & Daglioglu, N. (2026). Predictive modeling of post‐blast <scp>TNT</scp> residue recovery using semi‐quantitative <scp>LC</scp> – <scp>MS</scp> / <scp>MS</scp> data and machine learning. Journal of Forensic Sciences. https://doi.org/10.1111/1556-4029.70511
Source records
- crossref · retrieved 2026-11-07T19:13:24.776Z