{"id":"W4391326684","doi":"10.1039/d3an02041j","title":"Time and spatially resolved VIS-NIR hyperspectral imaging as a novel monitoring tool for laser-based spectroscopy to mitigate radiation damage on paintings","year":2024,"lang":"en","type":"article","venue":"The Analyst","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Arts and Humanities Research Council; Trent University; Horizon 2020 Framework Programme; Nottingham Trent University","keywords":"Hyperspectral imaging; Imaging spectroscopy; Laser; Raman spectroscopy; Materials science; Chemical imaging; Optics; Spectroscopy; Laser-induced breakdown spectroscopy; Radiation; Optoelectronics; Remote sensing; Geology; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004154616,0.0001853072,0.0002278427,0.0001365227,0.0003900908,0.001103701,0.0001449527,0.00001985645,0.0003459745],"category_scores_gemma":[0.0000698271,0.0001273355,0.0001530104,0.0001016939,0.00008160644,0.0001718682,0.00003060701,0.00008129837,0.0001067982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008596174,"about_ca_system_score_gemma":0.00002829472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008657989,"about_ca_topic_score_gemma":0.0003326751,"domain_scores_codex":[0.9989734,0.00004419211,0.0002375537,0.0003089826,0.0001770176,0.000258848],"domain_scores_gemma":[0.9994255,0.0001794426,0.00006039662,0.0002099654,0.00006983081,0.00005488054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002619844,0.00006441738,0.0000899046,0.0001363676,0.0003606804,0.0000238122,0.01667924,0.001330416,0.9628528,0.01395072,0.001996206,0.002253482],"study_design_scores_gemma":[0.002345757,0.001069427,0.001560108,0.001383249,0.002716178,0.000008959239,0.008459925,0.2973067,0.5715098,0.002244236,0.1093711,0.002024499],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993542,0.0001029386,0.0003212779,0.004218431,0.0001974955,0.0003247105,0.00009580343,0.0001402499,0.001057053],"genre_scores_gemma":[0.9953445,0.000006348095,0.0006607528,0.0003696591,0.001321691,0.00003779885,0.00004707144,0.00003448086,0.002177676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.391343,"threshold_uncertainty_score":0.9999332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764688216755568,"score_gpt":0.2528423094566057,"score_spread":0.23519542728905,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}