{"id":"W3189038708","doi":"10.1145/3460881.3460934","title":"PenShaft: Enabling Pen Shaft Detection and Interaction for Touchscreens","year":2021,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Waterloo; Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Human–computer interaction","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":[0.00008179543,0.00007868712,0.000085511,0.0000606503,0.0001401541,0.000160092,0.0001134492,0.00003309955,0.00007897739],"category_scores_gemma":[0.00009924609,0.00007508894,0.00005768293,0.0001147296,0.000008821183,0.000834494,0.0001221873,0.0000776936,0.00002746729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003124367,"about_ca_system_score_gemma":0.00002166363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004536117,"about_ca_topic_score_gemma":0.00009777632,"domain_scores_codex":[0.9993498,0.00002606168,0.0001080457,0.0002916069,0.00007222644,0.0001522244],"domain_scores_gemma":[0.9993835,0.0001373269,0.00004206327,0.000168834,0.0002264321,0.00004186228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006324705,0.00006700941,0.000330698,0.00003134305,0.00006090647,0.000017844,0.000895201,0.00001793395,0.9249644,0.01936667,0.001478269,0.0527065],"study_design_scores_gemma":[0.0004927371,0.0001711553,0.006490644,0.00002759553,0.00001576991,0.0001496649,0.00120454,0.05774322,0.9140105,0.002023364,0.01744799,0.0002227994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06820222,0.00004786369,0.9224814,0.00080012,0.0004701657,0.0001232594,0.000001923904,0.00002434905,0.007848722],"genre_scores_gemma":[0.9912117,0.00001418268,0.006365174,0.0007399433,0.00008463332,0.00001628935,0.000004837463,0.000005625992,0.001557627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9230095,"threshold_uncertainty_score":0.3062038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02556442194576651,"score_gpt":0.2923758703600274,"score_spread":0.2668114484142609,"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."}}