{"id":"W4408765490","doi":"10.1007/s00146-025-02290-1","title":"The model is the museum: generative AI and the expropriation of cultural heritage","year":2025,"lang":"en","type":"article","venue":"AI & Society","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Expropriation; Performing arts; Cultural heritage; Generative grammar; Generative model; Generative Design; Cultural heritage management; Visual arts; Artificial intelligence; Aesthetics; Computer science; Art; History; Archaeology; Engineering; Political science; Law; Operations management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005795835,0.00008605311,0.0000976013,0.000002030758,0.0008435462,0.0001237063,0.0001624594,0.00004741538,0.00003042017],"category_scores_gemma":[0.0000281292,0.00003044431,0.0001142706,0.0001294978,0.000366941,0.0001373617,0.00001907251,0.0001717855,0.000004729993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003321783,"about_ca_system_score_gemma":0.00003226925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007689834,"about_ca_topic_score_gemma":0.0009127751,"domain_scores_codex":[0.9993032,0.0001475516,0.0001366679,0.0001255332,0.0001500348,0.0001370092],"domain_scores_gemma":[0.9994993,0.0002023647,0.00004992932,0.0001559311,0.00007474591,0.00001772893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002976141,0.00004347653,0.07124286,0.0001030747,0.000699524,0.000001071434,0.3526556,0.0106044,0.001295386,0.013114,0.4547868,0.09515615],"study_design_scores_gemma":[0.001021136,0.00004438473,0.07630966,0.00002881642,0.00006628657,0.000002579143,0.0406006,0.861622,0.0005481695,0.00987086,0.009679081,0.000206472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9265742,0.006524723,0.001027426,0.06161157,0.0002923275,0.00045288,0.00008355517,0.00003716396,0.003396105],"genre_scores_gemma":[0.9902487,0.0009907497,0.0001665123,0.006448793,0.00003801271,0.000003852037,0.00001348789,0.000001264252,0.002088602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8510175,"threshold_uncertainty_score":0.6487961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01450628538768838,"score_gpt":0.2402494835298771,"score_spread":0.2257431981421887,"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."}}