{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:34:07Z","timestamp":1792787647704,"version":"4.5.0"},"reference-count":31,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T00:00:00Z","timestamp":1784678400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"The Research Start-up Fund for High-Level Talents of Hebei University","award":["521100225242"],"award-info":[{"award-number":["521100225242"]}],"id":[{"id":"https:\/\/ror.org\/01p884a79","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Hebei Natural Science Foundation","award":["F2026201070"],"award-info":[{"award-number":["F2026201070"]}]},{"name":"President\u2019s Foundation of Hebei University","id":[{"id":"https:\/\/ror.org\/01p884a79","id-type":"ROR","asserted-by":"crossref"}]},{"name":"the Multidisciplinary Interdisciplinary Research Fund of Hebei University","award":["DXK202312"],"award-info":[{"award-number":["DXK202312"]}],"id":[{"id":"https:\/\/ror.org\/01p884a79","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Appl Spectrosc"],"abstract":"<jats:p>\n                    The combination of laser-induced breakdown spectroscopy (LIBS) and machine learning provides a rapid approach for coal ash quantification. However, in practical coal preparation plants, calibration samples are often limited, and ash contents are usually confined to a narrow range, making reliable quantitative modeling difficult. To address this issue, we propose a structured spectral in-context learning framework for small-sample coal ash quantification. Unlike conventional methods that rely on task-specific iterative parameter optimization, the proposed framework performs downstream inference by conditioning on a limited set of calibration samples using a pre-trained tabular foundation model. To adapt continuous high-dimensional LIBS spectra to this framework, segmented statistical descriptors and multi-scale Haar-like features were constructed to capture subtle local spectral variations associated with narrow ash-content changes. The experimental results show that the proposed SS-ICL framework achieves robust predictive performance under restricted conditions, with an R\n                    <jats:sup>2<\/jats:sup>\n                    of 0.8880 and an RMSE of 0.1953 in a narrow-range washed-coal scenario. These results demonstrate that the proposed framework provides a practical and robust strategy for on-site LIBS-based coal quality analysis in restricted industrial environments.\n                  <\/jats:p>","DOI":"10.1177\/00037028261474584","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T18:49:04Z","timestamp":1784746144000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["An in-Context Learning Framework for Small-Sample Coal Ash Quantification via Laser-Induced Breakdown Spectroscopy"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9612-068X","authenticated-orcid":false,"given":"Bo","family":"Cheng","sequence":"first","affiliation":[{"name":"Hebei University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhoushuai","family":"Chen","sequence":"additional","affiliation":[{"name":"Hainan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cunguang","family":"Lou","sequence":"additional","affiliation":[{"name":"Hebei University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2496-6144","authenticated-orcid":false,"given":"Yunfei","family":"Li","sequence":"additional","affiliation":[{"name":"Hebei University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruikai","family":"Li","sequence":"additional","affiliation":[{"name":"Hebei University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,7,22]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsomega.5c03962"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12517-023-11552-5"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2023.165985"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fuel.2018.08.134"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.radphyschem.2025.112693"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/app13148158"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fuel.2022.125991"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2020.164449"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2019.164001"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphy.2022.1054796"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1039\/D0JA00186D"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sab.2017.09.010"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1039\/D1JA00179E"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sab.2021.106142"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.3390\/app131810049"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1039\/D0AY00905A"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.3390\/s24061833"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1039\/D2JA00204C"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fuel.2021.121667"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11467-024-1427-2"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1039\/D4JA00250D"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/s44211-024-00610-x"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1039\/D5JA00490J"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1039\/D5JA00011D"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.64"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-emnlp.590"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-63797-1_23"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2024.114731"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sab.2015.09.022"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sab.2019.105688"},{"key":"e_1_3_2_32_2","unstructured":"Zheng L. LIBS pollutant dataset for coal chemical industry (V1). Nanjing Tech University (creator) 2024. National Science Data Center (publisher). Available at: https:\/\/cstr.cn\/16666.11.nbsdc.BWOiPnu8"}],"container-title":["Applied Spectroscopy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00037028261474584","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/00037028261474584","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00037028261474584","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T14:33:29Z","timestamp":1790519609000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/00037028261474584"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,22]]},"references-count":31,"alternative-id":["10.1177\/00037028261474584"],"URL":"https:\/\/doi.org\/10.1177\/00037028261474584","relation":{},"ISSN":["0003-7028","1943-3530"],"issn-type":[{"value":"0003-7028","type":"print"},{"value":"1943-3530","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,22]]},"article-number":"00037028261474584"}}