{"id":"W4402483999","doi":"10.1016/j.culher.2024.08.014","title":"Machine learning in analytical chemistry for cultural heritage: A comprehensive review","year":2024,"lang":"en","type":"review","venue":"Journal of Cultural Heritage","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Narodowe Centrum Nauki","keywords":"Cultural heritage; Engineering; Engineering ethics; Management science; Archaeology; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001665599,0.001026961,0.001925744,0.002695227,0.0002885368,0.001428888,0.001178919,0.001482182,0.003232913],"category_scores_gemma":[0.002590075,0.0003976329,0.001043037,0.003234396,0.0005762005,0.002115734,0.00100133,0.00180531,0.001292313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005936159,"about_ca_system_score_gemma":0.002083737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001702341,"about_ca_topic_score_gemma":0.002953191,"domain_scores_codex":[0.9996274,0.00008008824,0.00004830733,0.00007801634,0.0001338774,0.00003245992],"domain_scores_gemma":[0.9983438,0.001086742,0.0001519047,0.00003679383,0.0003142316,0.00006656226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005314422,0.00009248773,0.0002633399,0.03277531,0.0002577197,0.0000903712,0.00004957471,0.0007003209,0.001232673,0.003119665,0.02476888,0.9365966],"study_design_scores_gemma":[0.00004237974,0.0001883976,0.001351476,0.01289716,0.0008402484,0.0006648249,0.00008700469,0.000813284,0.001666751,0.004088252,0.9772878,0.00007247625],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008073487,0.9988785,0.0003721854,0.0002054469,0.000122621,0.000004722835,0.00001932013,0.000008537924,0.0003078244],"genre_scores_gemma":[0.0005481002,0.9984999,0.0004169046,0.0001672545,0.0001535394,0.000005090646,0.00002788756,0.000001980294,0.0001793806],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003232913,"threshold_uncertainty_score":0.0108152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1170935972842597,"score_gpt":0.3627437917913747,"score_spread":0.245650194507115,"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."}}