{"id":"W2111318059","doi":"10.1109/icdar.2009.251","title":"Pen Acoustic Emissions for Text and Gesture Recognition","year":2009,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Cursive; Speech recognition; Gesture; Similarity (geometry); Artificial intelligence; SIGNAL (programming language); Template matching; Pattern recognition (psychology); Image (mathematics)","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":[0.0001524597,0.00009460425,0.00009998964,0.00008431612,0.0001266844,0.0001313318,0.0002142609,0.00007945823,0.00005826303],"category_scores_gemma":[0.0001026366,0.00007876796,0.00003636132,0.0001364435,0.00001575365,0.0003619714,0.00004255907,0.00007699256,0.00002850633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000130072,"about_ca_system_score_gemma":0.00002413615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002695647,"about_ca_topic_score_gemma":0.00000322221,"domain_scores_codex":[0.9993211,0.00001881988,0.0001311603,0.0002665757,0.00009399251,0.0001683207],"domain_scores_gemma":[0.9994543,0.0001063096,0.00003775403,0.0001914524,0.000110602,0.00009954165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003795367,0.00004702661,0.00001117038,0.000009050944,0.000003306998,0.000002243646,0.0001196775,2.544754e-7,0.009991782,0.002272831,0.01703174,0.9705071],"study_design_scores_gemma":[0.001717432,0.001668049,0.008898454,0.0002707359,0.00006165461,0.0002858251,0.0001547256,0.03088988,0.1543458,0.7757616,0.02474255,0.001203327],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00363453,0.00004907433,0.9829811,0.00376777,0.0000467327,0.0003858588,0.000005687477,0.0006174034,0.008511839],"genre_scores_gemma":[0.618917,0.00006184021,0.3769794,0.002607798,0.00006902496,0.00005545301,0.00001327702,0.000006582042,0.001289647],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9693038,"threshold_uncertainty_score":0.3212064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315801403522359,"score_gpt":0.2754912154432502,"score_spread":0.2523332014080266,"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."}}