{"id":"W1504007998","doi":"10.2312/vissym/eurovis07/043-050","title":"KeyStrokes: Personalizing Typed Text with Visualization","year":2007,"lang":"en","type":"article","venue":"Eurographics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Handwriting; Style (visual arts); Human–computer interaction; Information visualization; Data visualization; World Wide Web; Artificial intelligence","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":[0.0003965372,0.0001113257,0.00008986051,0.0002470333,0.0001315967,0.0002205936,0.0003959664,0.00003990775,0.00001620703],"category_scores_gemma":[0.00004018555,0.00009591292,0.00004040861,0.001581757,0.00006468972,0.0004091961,0.00006477584,0.00008272925,0.00004173891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001013768,"about_ca_system_score_gemma":0.00003321046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005026401,"about_ca_topic_score_gemma":0.00002118117,"domain_scores_codex":[0.9989507,0.00003286372,0.000171268,0.000256269,0.0003507994,0.0002381081],"domain_scores_gemma":[0.9992808,0.00005030781,0.00008646061,0.0003086689,0.0001688546,0.0001049621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001054677,0.0001253185,0.01505992,0.00002386399,0.00003695669,0.00004832501,0.001052271,0.00001677283,0.0004054163,0.9758693,0.001620833,0.005730493],"study_design_scores_gemma":[0.003126892,0.001354907,0.04819405,0.00026417,0.0001274876,0.0002129223,0.002220624,0.2400265,0.004785261,0.002421481,0.6951832,0.002082571],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006702815,0.00005259816,0.9868619,0.0001460096,0.0001085618,0.00006661371,0.00000195121,0.0002700165,0.005789568],"genre_scores_gemma":[0.9412482,0.00007508456,0.05616429,0.001757506,0.0001288527,0.000001961324,0.00005626109,0.00003258817,0.0005351923],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9734478,"threshold_uncertainty_score":0.3911215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01926803594039424,"score_gpt":0.2909504516757582,"score_spread":0.271682415735364,"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."}}