{"id":"W4391597766","doi":"10.32920/25164602.v1","title":"AR Fitting Room and Beyond","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Process (computing); Selection (genetic algorithm); Human–computer interaction; World Wide Web; Artificial intelligence","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":[0.000199553,0.0001306579,0.0001261244,0.00007859092,0.00006523652,0.0003875039,0.0006751728,0.0001258526,0.00001642213],"category_scores_gemma":[0.00001194919,0.0001172363,0.00004582352,0.0001349079,0.00002499744,0.0000481799,0.00569573,0.0004579827,0.000114698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003471708,"about_ca_system_score_gemma":0.00008152366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006403595,"about_ca_topic_score_gemma":0.00001667536,"domain_scores_codex":[0.9989153,0.0000192793,0.0001815386,0.0005919043,0.0001512901,0.0001407051],"domain_scores_gemma":[0.9990075,0.00006169903,0.00005574516,0.0007757443,0.00002953294,0.00006980769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[1.835096e-7,0.00002249435,0.00001784316,0.0001707826,0.00004924904,0.000007064378,0.0007054389,0.0003621659,0.000090548,0.9109798,0.01452871,0.07306572],"study_design_scores_gemma":[0.00004429952,0.0000072783,0.0001597112,0.00007268474,0.00002112504,0.00001485674,0.00004287691,0.3694744,0.0005000188,0.6157687,0.01363891,0.0002552299],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001097458,0.0006364812,0.8953433,0.01354719,0.0003368113,0.000269988,0.00001089596,0.0005465223,0.08821136],"genre_scores_gemma":[0.543429,0.0002689701,0.4353542,0.002732677,0.0004652279,0.0003853875,0.00005086864,0.00005317256,0.01726043],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5423316,"threshold_uncertainty_score":0.7099319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749560432932921,"score_gpt":0.2726089812053544,"score_spread":0.2551133768760252,"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."}}