{"id":"W1036937704","doi":"","title":"Surveillance video retrieval: what we have already done?","year":2010,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Francophone University Association","funders":"","keywords":"Computer science; Information retrieval; Domain (mathematical analysis); Event (particle physics); Object (grammar); Video retrieval; Point (geometry); Image retrieval; Object detection; Image (mathematics); Artificial intelligence; Pattern recognition (psychology)","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004923642,0.000294983,0.0003123078,0.0001812588,0.0003993492,0.00115664,0.002381281,0.0001932044,0.00007760489],"category_scores_gemma":[0.002195287,0.0002936345,0.0001551327,0.0008264295,0.0002705735,0.002062394,0.0008660153,0.0006440053,0.00009080866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005298234,"about_ca_system_score_gemma":0.0001341964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001617518,"about_ca_topic_score_gemma":0.0007391233,"domain_scores_codex":[0.9959589,0.001692264,0.0004683757,0.0008385288,0.0005413784,0.0005006043],"domain_scores_gemma":[0.9929572,0.001673355,0.0003280613,0.002938552,0.001849065,0.0002537776],"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":[0.00002666952,0.0005543138,0.002711147,0.00005722531,0.00004155197,0.00002832687,0.005273708,0.00000257377,0.1160711,0.260491,0.003746836,0.6109955],"study_design_scores_gemma":[0.0005217374,0.000001617815,0.00260064,0.0004017492,0.000006985027,0.00004986085,0.00008067764,0.00659899,0.7990093,0.02072365,0.1694289,0.0005758193],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01296658,0.001386277,0.9496795,0.02059345,0.0004090017,0.0003381201,0.000008126558,0.0009363102,0.01368265],"genre_scores_gemma":[0.6744958,0.004021463,0.3121392,0.0005004057,0.00005178197,0.00002759222,0.00004612449,0.0000526182,0.008665038],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6829382,"threshold_uncertainty_score":0.9999516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200642384886242,"score_gpt":0.2477103840766177,"score_spread":0.2357039602277553,"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."}}