{"id":"W4384824348","doi":"10.1007/s13735-023-00280-x","title":"Cluster-guided temporal modeling for action recognition","year":2023,"lang":"en","type":"article","venue":"International Journal of Multimedia Information Retrieval","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Institute for Information and Communications Technology Promotion; National Research Foundation of Korea","keywords":"Computer science; Artificial intelligence; Action recognition; Classifier (UML); Cluster analysis; Redundancy (engineering); Pattern recognition (psychology); Benchmark (surveying); Computer vision","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":[0.0005625107,0.0008604771,0.001243038,0.001049951,0.0006589963,0.0007854024,0.002240763,0.0009846212,0.003866246],"category_scores_gemma":[0.001484117,0.0005858056,0.001497772,0.001760686,0.0004636322,0.0007827205,0.0007684664,0.001340012,0.001501466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001343306,"about_ca_system_score_gemma":0.001849054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06045412,"about_ca_topic_score_gemma":0.05859032,"domain_scores_codex":[0.999671,0.00005216377,0.00001867728,0.0001212512,0.0000663454,0.00007057765],"domain_scores_gemma":[0.9994016,0.0002750453,0.00005376906,0.00007498718,0.0001504136,0.00004414537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003667494,0.0001574443,0.001091642,0.00008136973,0.0001497451,0.00008027623,0.00007260111,0.7898519,0.01001051,0.00911276,0.006110333,0.1829147],"study_design_scores_gemma":[0.000001911329,0.000006111675,0.00006677333,0.000001488767,0.000005267915,0.000006230404,0.000003949251,0.9976352,0.0005618198,0.001466932,0.000241255,0.000003031196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01494924,0.0003441514,0.9809477,0.0001320596,0.0000726281,0.00004495159,0.0004579641,0.002150428,0.0009009303],"genre_scores_gemma":[0.6545669,0.0007201272,0.332253,0.0002848169,0.0001288213,0.0003343183,0.002674887,0.0009385886,0.008098392],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06045412,"threshold_uncertainty_score":0.1202045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09175955666872154,"score_gpt":0.3422098726154404,"score_spread":0.2504503159467188,"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."}}