{"id":"W2346459493","doi":"10.1145/2851581.2892444","title":"FlexStylus","year":2016,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Stylus; FLEX; Computer science; Analog device; Tactile sensor; Input device; Proximity sensor; Computer graphics (images); Computer vision; Artificial intelligence; Computer hardware; Analog signal; Digital signal processing; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007097431,0.001086169,0.0007833858,0.001278731,0.0005903384,0.001265156,0.00164481,0.0007813348,0.06069889],"category_scores_gemma":[0.00217945,0.0006748121,0.0004955858,0.000744192,0.0007044123,0.002475585,0.003029463,0.001078597,0.01238419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005318819,"about_ca_system_score_gemma":0.0008407267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256467,"about_ca_topic_score_gemma":0.001234476,"domain_scores_codex":[0.999221,0.00006383716,0.00003768013,0.0001912146,0.0004024403,0.00008382949],"domain_scores_gemma":[0.9989518,0.0002178169,0.00008155196,0.000274014,0.0002541767,0.0002207062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002466662,0.0002276515,0.004588823,0.001151762,0.00006146909,0.0009258452,0.0009068223,0.00192092,0.1797099,0.02050142,0.1122362,0.6753025],"study_design_scores_gemma":[0.000576076,0.002338218,0.01498898,0.0004120011,0.0001407041,0.009827384,0.0002773194,0.02163949,0.1690904,0.007629355,0.7726801,0.0003999553],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.1618791,0.005381133,0.4459909,0.001572787,0.001564629,0.002272594,0.0118445,0.122059,0.2474355],"genre_scores_gemma":[0.5152283,0.002256529,0.2229145,0.00141519,0.000335956,0.001292482,0.01202696,0.008465652,0.2360643],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06069889,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00791862544732555,"score_gpt":0.226667411121601,"score_spread":0.2187487856742755,"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."}}