{"id":"W4393993814","doi":"10.3390/info15040203","title":"Explainable Machine Learning Method for Aesthetic Prediction of Doors and Home Designs","year":2024,"lang":"en","type":"article","venue":"Information","topic":"Cultural Heritage Management and Preservation","field":"Arts and Humanities","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Doors; Machine learning; Classifier (UML); Computer science; Random forest; Artificial intelligence; Context (archaeology); Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002463899,0.00004435363,0.00005032233,0.00008313272,0.0001176711,0.0001817763,0.00002373337,0.00001609929,0.0001189463],"category_scores_gemma":[0.00001172213,0.00003512354,0.00002172382,0.00002721547,0.00001468063,0.00160399,0.00001154287,0.00003714887,0.000007469241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001037772,"about_ca_system_score_gemma":0.000002985852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000118284,"about_ca_topic_score_gemma":0.00002435318,"domain_scores_codex":[0.999683,0.00001417928,0.0001477828,0.00003674343,0.0000628286,0.00005544115],"domain_scores_gemma":[0.9998384,0.00003111798,0.00003998036,0.00002908642,0.00005207962,0.00000932321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005821954,0.000008456919,0.0001494317,0.001307444,0.00003210057,2.376321e-7,0.1083865,0.0006687902,0.0001241797,0.607912,0.005330147,0.2760225],"study_design_scores_gemma":[0.0001504751,0.000117425,0.00008813589,0.00004428762,0.00002285615,0.000001140042,0.003029938,0.2286046,0.00007032078,0.004298542,0.7635235,0.00004879231],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2970568,0.002672538,0.4909174,0.003140936,0.002464266,0.003468164,0.000393196,0.001249117,0.1986376],"genre_scores_gemma":[0.9925703,0.00005345059,0.002002436,0.00004791468,0.00008581574,0.00005568954,0.0004556915,0.000005784489,0.004722878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7581933,"threshold_uncertainty_score":0.1752873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08642650201027106,"score_gpt":0.2525914651551889,"score_spread":0.1661649631449179,"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."}}