{"id":"W1992120605","doi":"10.1145/2614217.2630586","title":"How personal video navigation history can be visualized","year":2014,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computer vision; Computer graphics (images); Multimedia; Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003854585,0.0005856697,0.0003348016,0.002192167,0.0004728004,0.001891652,0.000485593,0.0008613261,0.2393547],"category_scores_gemma":[0.003780505,0.0002472558,0.0002804034,0.00215813,0.0001939249,0.0020204,0.0007996929,0.0006388805,0.06512502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002515736,"about_ca_system_score_gemma":0.0005311511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003995734,"about_ca_topic_score_gemma":0.007681012,"domain_scores_codex":[0.9998395,0.00003683701,0.0000120794,0.00003341621,0.0000569913,0.00002118602],"domain_scores_gemma":[0.9989279,0.0003815791,0.00005466327,0.0001806294,0.0003356041,0.0001196735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000600154,0.00005372058,0.001421477,0.001343677,0.00002625979,0.0006457681,0.0006212195,0.0005973207,0.01316677,0.004848039,0.5026352,0.4740404],"study_design_scores_gemma":[0.00005916217,0.0001280039,0.008266561,0.000793865,0.00007254482,0.00101569,0.0007052153,0.003871282,0.01344366,0.00770678,0.9638587,0.0000785076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02338433,0.009304079,0.1833067,0.008801972,0.007113911,0.001558705,0.1192337,0.03941062,0.607886],"genre_scores_gemma":[0.2542576,0.01742774,0.1606218,0.002403725,0.002692809,0.001184038,0.07865291,0.009872611,0.4728868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2393547,"threshold_uncertainty_score":0.8007213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841515805946739,"score_gpt":0.2406029452975002,"score_spread":0.2221877872380328,"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."}}