{"id":"W2107433507","doi":"10.1109/icdar.2007.4377116","title":"Streaming-Archival InkML Conversion","year":2007,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Document Analysis and Recognition","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Markup language; Computer science; Inkwell; Streaming data; Style (visual arts); World Wide Web; Multimedia; XML; Data mining; Operating system; Art","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":[0.000441035,0.00008765811,0.0001153965,0.0004530678,0.00007859682,0.0002057352,0.0005231039,0.00002941714,0.00003215226],"category_scores_gemma":[0.00002039055,0.00006323079,0.000114544,0.000514153,0.00004510489,0.0003056846,0.0002405441,0.00007986665,0.00000146021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002197996,"about_ca_system_score_gemma":0.000009935959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003405564,"about_ca_topic_score_gemma":0.000006002118,"domain_scores_codex":[0.9990528,0.000005325971,0.0002401138,0.0002240643,0.0003856478,0.00009201194],"domain_scores_gemma":[0.9991953,0.00003270025,0.000239736,0.0000714101,0.0004223126,0.00003858774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002814151,0.00009420409,0.01367485,0.00001576844,0.0003250213,3.585834e-7,0.0003980438,6.725446e-7,0.004654923,0.9197434,0.0001777945,0.0608868],"study_design_scores_gemma":[0.0006977457,0.0003581203,0.08423816,0.0002929824,0.0003048665,0.000007927963,0.0003483339,0.1226167,0.3510738,0.4390667,0.0005303654,0.000464217],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8350933,0.00000679695,0.15117,0.001105646,0.0002239343,0.0001495974,0.000004320809,0.00006849148,0.01217802],"genre_scores_gemma":[0.9972388,0.0001110562,0.002344617,0.000138913,0.00003109519,0.000003064592,0.000007656185,0.00000243124,0.0001223854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4806767,"threshold_uncertainty_score":0.2578477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609234672287807,"score_gpt":0.2920136010725759,"score_spread":0.2659212543496978,"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."}}