{"id":"W4413983003","doi":"10.2139/ssrn.5440547","title":"A Deep Dive into Generic Object Tracking: A Survey","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Tracking (education); Computer science; Object (grammar); Artificial intelligence; Computer vision; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005033006,0.001457293,0.002983867,0.003076314,0.0009846658,0.003867395,0.003548673,0.003280121,0.00346878],"category_scores_gemma":[0.01355532,0.00161606,0.001549437,0.006607773,0.002012431,0.008110327,0.002767733,0.002383399,0.00301743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358646,"about_ca_system_score_gemma":0.00195854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003898785,"about_ca_topic_score_gemma":0.002195034,"domain_scores_codex":[0.996681,0.000617773,0.0002465141,0.001448028,0.000845739,0.0001609191],"domain_scores_gemma":[0.9898761,0.006161744,0.0003932238,0.001961515,0.001320606,0.000286926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001039204,0.000111775,0.002785965,0.002329555,0.0001281844,0.00005300228,0.0002215041,0.01006758,0.002126798,0.03811738,0.01056443,0.93339],"study_design_scores_gemma":[0.0000531363,0.0007631851,0.0109621,0.002900239,0.0003783138,0.002384327,0.0007535971,0.2353583,0.008620954,0.2100864,0.5275338,0.0002057781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.008672238,0.3188451,0.6532439,0.002817533,0.0005704166,0.0001015228,0.0003115842,0.0009546824,0.01448302],"genre_scores_gemma":[0.1436258,0.4982853,0.3367839,0.003460139,0.003167686,0.0001883259,0.002344151,0.0008036399,0.0113411],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005033006,"threshold_uncertainty_score":0.02661735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0308127199091336,"score_gpt":0.3127418006977451,"score_spread":0.2819290807886115,"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."}}