{"id":"W4225102272","doi":"10.1145/3491101.3519796","title":"Everywhere Cursor: Extending Desktop Mouse Interaction into Spatial Augmented Reality","year":2022,"lang":"en","type":"article","venue":"CHI Conference on Human Factors in Computing Systems Extended Abstracts","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cursor (databases); Human–computer interaction; Augmented reality; Computer graphics (images); Virtual desktop; 3D interaction; Mixed reality; Virtual reality; Input device; Virtual machine; Computer vision; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001017066,0.0005557312,0.0006232692,0.0006226631,0.001157163,0.0005645947,0.001582647,0.0001278707,0.0001176852],"category_scores_gemma":[0.0001283354,0.0005776456,0.0001961497,0.0004149936,0.00007978094,0.0008258427,0.0007308758,0.001412223,0.00004400577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394405,"about_ca_system_score_gemma":0.0001800272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004548761,"about_ca_topic_score_gemma":0.0001988498,"domain_scores_codex":[0.9951678,0.000781008,0.001150336,0.001237486,0.0008807608,0.0007826184],"domain_scores_gemma":[0.9973425,0.0003292937,0.0009598571,0.0009419644,0.0002273412,0.0001990055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007205487,0.006814607,0.02335366,0.0009417642,0.0007462478,0.0009747803,0.06332123,0.1931072,0.292905,0.3791354,0.005827339,0.03215216],"study_design_scores_gemma":[0.004779839,0.002708272,0.5104022,0.002040885,0.00005997204,0.0002211534,0.02173563,0.3826664,0.06309374,0.005001911,0.0031832,0.004106789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606948,0.00003686038,0.02740827,0.0001216548,0.003828946,0.0006930386,0.00002656064,0.0001951404,0.006994718],"genre_scores_gemma":[0.9991208,0.000003544431,0.0001296976,0.0001111457,0.0001642344,0.00004214704,0.0001107248,0.00003795899,0.0002797179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4870486,"threshold_uncertainty_score":0.9996675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08079925528118564,"score_gpt":0.3436025089178089,"score_spread":0.2628032536366233,"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."}}