{"id":"W2978525497","doi":"10.1145/3338286.3340122","title":"WatchPen","year":2019,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Stylus; Computer science; Smartwatch; Human–computer interaction; Context (archaeology); Mobile device; Capacitive sensing; Touchpad; Selection (genetic algorithm); Mobile interaction; Input device; Artificial intelligence; Computer hardware; Embedded system; Wearable computer; Computer vision; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003019799,0.0008739529,0.0004056965,0.0007123082,0.000449308,0.001828748,0.0009600167,0.0007005275,0.1351811],"category_scores_gemma":[0.001559854,0.000350208,0.0004036877,0.0007109224,0.0003525556,0.001818961,0.002332157,0.0006006964,0.03395813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002123236,"about_ca_system_score_gemma":0.0003108214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005332532,"about_ca_topic_score_gemma":0.001215876,"domain_scores_codex":[0.9996835,0.00003859478,0.00001928616,0.00008959121,0.0001335142,0.00003552752],"domain_scores_gemma":[0.9994054,0.0001694633,0.00003109197,0.0002152474,0.0001054966,0.00007334726],"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":[0.0008041271,0.00009917185,0.001713137,0.001539017,0.00006522296,0.001173819,0.001335121,0.001854817,0.1345639,0.07149445,0.1552704,0.6300869],"study_design_scores_gemma":[0.00003893326,0.0001488716,0.001678517,0.0001197514,0.00003377867,0.0008059511,0.0001941349,0.004666207,0.03893559,0.004846216,0.9484909,0.00004110164],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03144314,0.003057243,0.4900243,0.0009165737,0.001284803,0.0006821799,0.007940838,0.05706073,0.4075902],"genre_scores_gemma":[0.2595399,0.003167699,0.1720908,0.00125081,0.0003135167,0.000886312,0.01173476,0.008565791,0.5424504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1351811,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003730243681098213,"score_gpt":0.2101778890016931,"score_spread":0.2064476453205949,"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."}}