{"id":"W2981668542","doi":"10.1017/s1930297500004861","title":"The glow of grime: Why cleaning an old object can wash away its value","year":2019,"lang":"en","type":"article","venue":"Judgment and Decision Making","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Object (grammar); Value (mathematics); Artificial intelligence; Computer science; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001971766,0.0002071346,0.0002347364,0.0004107592,0.000823702,0.001796617,0.0005215997,0.001054053,0.004192747],"category_scores_gemma":[0.01261822,0.0002799349,0.0002872328,0.0002128646,0.003818874,0.002251656,0.001134235,0.001185898,0.0002756387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000630885,"about_ca_system_score_gemma":0.0003316544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001211074,"about_ca_topic_score_gemma":0.002551588,"domain_scores_codex":[0.9989402,0.0003306478,0.00003831744,0.0001798805,0.0003961335,0.0001147522],"domain_scores_gemma":[0.9958616,0.001932643,0.0007421524,0.0006387465,0.0005404986,0.000284427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004493852,0.000448561,0.1565318,0.001554324,0.0004961209,0.002600495,0.07135183,0.002709544,0.3338376,0.2108168,0.008468308,0.2066908],"study_design_scores_gemma":[0.0001748027,0.001351257,0.4524102,0.0006288965,0.0003397479,0.002852979,0.04761936,0.01179327,0.06936124,0.3595446,0.05362887,0.000294863],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.954444,0.0006341523,0.01037714,0.00163477,0.0001064523,0.00001479867,0.00002429992,0.00003055704,0.03273392],"genre_scores_gemma":[0.9963773,0.00008812364,0.002448224,0.0001636418,0.000008295129,0.000003709132,0.00001134268,0.00001627068,0.0008830747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004192747,"threshold_uncertainty_score":0.01402611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03141405481658445,"score_gpt":0.3033134394187663,"score_spread":0.2718993846021818,"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."}}