{"id":"W4396833655","doi":"10.1145/3613905.3644069","title":"Traveling Arts x HCI Sketchbook: Exploring the Intersection Between Artistic Expression and Human-Computer Interaction","year":2024,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Fundação para a Ciência e a Tecnologia; UK Research and Innovation; Marcus och Amalia Wallenbergs minnesfond; Engineering and Physical Sciences Research Council; Irish Research Council; European Commission","keywords":"The arts; Intersection (aeronautics); Visual arts; Expression (computer science); Variety (cybernetics); Sociology; Computer science; Art; Aesthetics; Engineering; 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":[0.0003634976,0.0001922907,0.0001467368,0.0002580955,0.0003652955,0.0005780612,0.0003375169,0.00007844104,0.00003757355],"category_scores_gemma":[0.00002167265,0.0001388253,0.00005358096,0.0003537499,0.00007671148,0.001926527,0.0003039592,0.0005989562,0.00009834269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001482765,"about_ca_system_score_gemma":0.00001383518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003020441,"about_ca_topic_score_gemma":0.0000151348,"domain_scores_codex":[0.9986164,0.00006924741,0.0003544338,0.0005381652,0.000183224,0.0002385205],"domain_scores_gemma":[0.9992088,0.00024546,0.00007784876,0.0003554622,0.00007906226,0.00003336341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000114661,0.00004500322,0.0005753253,0.00008908587,0.0001181362,0.00005173618,0.006453009,0.00008014619,0.1366835,0.374853,0.002935721,0.4781039],"study_design_scores_gemma":[0.0006634315,0.0009169776,0.02972664,0.002233535,0.00008975992,0.000671048,0.002192287,0.2684361,0.6078671,0.06306247,0.02283365,0.001307034],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.387188,0.00001771985,0.6087382,0.0005244811,0.00175084,0.0001201162,3.521458e-7,0.0005290949,0.001131111],"genre_scores_gemma":[0.9916832,0.000003634404,0.007289696,0.0001105193,0.0005526005,0.00006279582,0.000003649704,0.00001701358,0.0002768877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6044952,"threshold_uncertainty_score":0.5661132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08371838518154663,"score_gpt":0.3210826993554315,"score_spread":0.2373643141738849,"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."}}