{"id":"W6911953815","doi":"10.5281/zenodo.12749386","title":"Mixed reality in U.S. retail: A review: Analyzing the immersive shopping experiences, customer engagement, and potential economic implications","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Leverage (statistics); Transformative learning; Set (abstract data type); Customer engagement; Standardization; Customer experience; Immersive technology; Mixed reality","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001735115,0.0001035898,0.0001263025,0.0002154305,0.001946865,0.0004763353,0.001464841,0.00003189698,0.000543466],"category_scores_gemma":[0.0002190251,0.00009622893,0.00004037543,0.001198033,0.000168625,0.0003687038,0.001926397,0.0002281805,0.001546663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623325,"about_ca_system_score_gemma":0.000008612034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003465679,"about_ca_topic_score_gemma":0.0000022273,"domain_scores_codex":[0.9982317,0.0005161603,0.0003062278,0.0004816578,0.0001625807,0.0003016916],"domain_scores_gemma":[0.9988385,0.00005141313,0.0001335581,0.00074842,0.0001309597,0.00009712498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000139324,0.000130712,0.00005135535,0.0002526669,0.0001142918,0.00001295867,0.01442944,0.001308869,0.004854775,0.1099412,0.5377314,0.3311584],"study_design_scores_gemma":[0.0002985885,0.00003380248,0.006817846,0.0001015915,0.00002010718,0.0000561155,0.002819353,0.01606667,0.0001146201,0.0005064865,0.9729264,0.0002384579],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06074549,0.002772503,0.7096667,0.1438655,0.0004334157,0.005566375,0.0003765384,0.003227421,0.07334605],"genre_scores_gemma":[0.9930611,0.005202133,0.0002983933,0.0004039683,0.00005875191,0.000002731768,0.0005275155,0.0002483253,0.0001971085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9323156,"threshold_uncertainty_score":0.9993525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08447924407514404,"score_gpt":0.2916610513042334,"score_spread":0.2071818072290894,"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."}}