{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004738116,0.0008975694,0.0005042746,0.001515919,0.0005949716,0.002222889,0.001407997,0.0007162638,0.02701888],"category_scores_gemma":[0.002342852,0.0003311858,0.0006069003,0.00160515,0.0004711189,0.002045407,0.001956453,0.001071545,0.009888731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004422874,"about_ca_system_score_gemma":0.0006248346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008836519,"about_ca_topic_score_gemma":0.0008270954,"domain_scores_codex":[0.9991965,0.00005127113,0.00007093414,0.000121984,0.0004776336,0.00008168668],"domain_scores_gemma":[0.9986321,0.0001834572,0.00005374627,0.0006066984,0.000472691,0.00005121521],"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":[0.0006810345,0.0002201395,0.0008945073,0.0004431373,0.0000307546,0.000839836,0.0006326566,0.006984785,0.1812836,0.03368635,0.03888755,0.7354156],"study_design_scores_gemma":[0.0001004132,0.0001419051,0.001085193,0.00007931792,0.00003838217,0.001792327,0.0003226862,0.07343384,0.60857,0.01949506,0.2948398,0.0001010565],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02268665,0.0004071787,0.898515,0.0002614355,0.0005073639,0.0004316352,0.001749834,0.03570395,0.03973687],"genre_scores_gemma":[0.223754,0.0009868881,0.6775844,0.0004087952,0.000359175,0.000504401,0.006248163,0.004854595,0.08529967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02701888,"threshold_uncertainty_score":0.09038717,"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."}}