{"id":"W4253095926","doi":"10.32920/ryerson.14647053","title":"Seeing fashion through sound","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Museums and Cultural Heritage","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Exhibition; Visitor pattern; Sound (geography); Clothing; Visual arts; Artifact (error); Wearable computer; Compromise; Multimedia; Computer science; Art; Sociology; History; Acoustics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005100325,0.0004352165,0.000156404,0.0008236172,0.003573199,0.007348431,0.0003900084,0.001202742,0.01994823],"category_scores_gemma":[0.001315167,0.0002194245,0.0003890169,0.0004352776,0.00598983,0.003880474,0.003423678,0.001327876,0.002515757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009718006,"about_ca_system_score_gemma":0.0007110538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005488738,"about_ca_topic_score_gemma":0.01368993,"domain_scores_codex":[0.9996207,0.000134025,0.000007643389,0.00006982064,0.0000951652,0.00007258404],"domain_scores_gemma":[0.9996411,0.0001472339,0.00002125954,0.00006424934,0.00005874596,0.00006748882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003544485,0.00008897956,0.006997345,0.0005956803,0.00004693479,0.002810144,0.4249849,0.0004725455,0.02657356,0.2670965,0.05030112,0.2196779],"study_design_scores_gemma":[0.00002917046,0.000148446,0.007158754,0.0004099247,0.0000482762,0.001666209,0.1296056,0.0003295935,0.004464806,0.03746941,0.8186147,0.00005520418],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1526437,0.005263683,0.01888592,0.008659137,0.001384842,0.00005017224,0.0002095906,0.0006049144,0.8122981],"genre_scores_gemma":[0.8424764,0.003336848,0.00898443,0.001403412,0.0003467562,0.00003844885,0.00009510086,0.0002567591,0.1430618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01994823,"threshold_uncertainty_score":0.06673342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09422294082130572,"score_gpt":0.2649186021877868,"score_spread":0.1706956613664811,"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."}}