{"id":"W2001429429","doi":"10.1109/iccnc.2012.6167488","title":"Trends and opportunities in consumer video content navigation and analysis","year":2012,"lang":"en","type":"article","venue":"2012 International Conference on Computing, Networking and Communications (ICNC)","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Publication; Digital video; Multimedia; Video processing; The Internet; Digital content; Video tracking; World Wide Web; Telecommunications; Artificial intelligence; Advertising","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":[0.0008328067,0.0001678098,0.0002514376,0.0005785017,0.0002954243,0.0004137761,0.0006204941,0.0000731062,0.00001921638],"category_scores_gemma":[0.00001642453,0.00016456,0.00004747926,0.0004327087,0.0001607723,0.0007939138,0.000509571,0.000215122,0.000001883941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003612355,"about_ca_system_score_gemma":0.00002317001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001766099,"about_ca_topic_score_gemma":0.000138915,"domain_scores_codex":[0.9985503,0.0002954402,0.0004006896,0.0003000202,0.0002239851,0.0002295624],"domain_scores_gemma":[0.9985905,0.0002139345,0.0002391944,0.0006298906,0.0001779488,0.0001485855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007703263,0.0001332297,0.1162768,0.000003895205,0.0001945068,8.235872e-7,0.001612547,0.0001404174,0.0000287536,0.480924,0.00008531141,0.400592],"study_design_scores_gemma":[0.0002717023,0.00003546299,0.1369137,0.00008046823,0.00007764558,0.00001028469,0.0002714126,0.8551946,0.000003567644,0.001126703,0.00580283,0.0002115523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5296062,0.01316656,0.4081911,0.01687217,0.00108027,0.0003687146,0.00002970166,0.0003269952,0.03035832],"genre_scores_gemma":[0.9920398,0.002779117,0.004342858,0.0003230077,0.00007551253,0.00001115878,0.0001735101,0.000006724192,0.0002482867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8550542,"threshold_uncertainty_score":0.6710563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.170194966415441,"score_gpt":0.324239046526992,"score_spread":0.154044080111551,"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."}}