{"id":"W2100291131","doi":"10.1109/icsmc.2007.4414038","title":"Real-time automatic detection of vandalism behavior in video sequences","year":2007,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada; Concordia University","funders":"","keywords":"Computer science; Graffiti; Computer vision; Artificial intelligence; Object detection; Object (grammar); Feature extraction; Sequence (biology); Phone; Video tracking; 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":[],"consensus_categories":[],"category_scores_codex":[0.001942476,0.00008000968,0.0001656603,0.0001972238,0.00003024618,0.00002939999,0.0003092992,0.00005781657,0.00002711545],"category_scores_gemma":[0.000065508,0.00006852052,0.00004477829,0.0005354086,0.00003364416,0.0003074941,0.0000489567,0.00006712066,0.00001942045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003499083,"about_ca_system_score_gemma":0.00003249802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007230491,"about_ca_topic_score_gemma":0.0003673334,"domain_scores_codex":[0.9989637,0.00009901346,0.0003253767,0.0002042615,0.0002036463,0.0002039835],"domain_scores_gemma":[0.9992529,0.0002681164,0.00009383467,0.000295787,0.00004866114,0.00004069345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000006757502,0.0001000562,0.02665277,0.00002776749,0.000007207339,0.00006006456,0.0006641994,0.0000328176,0.3978145,0.002264593,0.00001417922,0.5723552],"study_design_scores_gemma":[0.0003059773,0.0001433667,0.6963302,0.00003106886,0.000005002196,0.00003305626,0.00003493703,0.01561758,0.2843212,0.002944721,0.00004952922,0.0001833201],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7104028,0.00001363647,0.2863652,0.00003587639,0.0001623923,0.0000931605,2.651295e-7,0.0001465376,0.002780159],"genre_scores_gemma":[0.8822921,0.000007784539,0.1175715,0.00002181806,0.00001611946,0.000005378602,2.746916e-7,0.000003772558,0.00008132878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6696774,"threshold_uncertainty_score":0.2794186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040524256812056,"score_gpt":0.3113138659785102,"score_spread":0.2909086234103897,"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."}}