{"id":"W2179553611","doi":"10.1002/047134608x.w8273","title":"Introduction to Human Action Recognition","year":2015,"lang":"en","type":"other","venue":"Wiley Encyclopedia of Electrical and Electronics Engineering","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Action (physics); Computer science; Action recognition; Task (project management); Benchmark (surveying); Representation (politics); Artificial intelligence; Data science; Engineering; Geography; Political science; Cartography","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":[0.0001337254,0.0001742407,0.0002039649,0.0004863214,0.00003490013,0.00003198326,0.0001462253,0.0001371377,0.0000736424],"category_scores_gemma":[0.00005155298,0.0001859604,0.00003445419,0.000577716,0.000007847262,0.0001666968,0.00003661097,0.0002386819,0.00004293804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007812666,"about_ca_system_score_gemma":0.00004958222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001815208,"about_ca_topic_score_gemma":0.00001502991,"domain_scores_codex":[0.9989606,0.00001959957,0.0001995757,0.0003354973,0.0001879963,0.0002967534],"domain_scores_gemma":[0.9995208,0.00001464473,0.00008387779,0.0001771362,0.00006138944,0.0001421669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001228075,0.0001170073,0.000007653546,0.00009497607,0.00007615134,0.000003347901,0.000110284,0.00007562179,0.006960352,0.01117956,0.631783,0.3495798],"study_design_scores_gemma":[0.0002100787,0.0003887189,0.00002485576,0.00005811334,0.0000232718,0.0000257482,0.000001710155,0.002048373,0.001677513,0.001905686,0.9933158,0.000320128],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01093482,0.01110299,0.5357258,0.00169693,0.002585223,0.001560494,0.00002825737,0.003090128,0.4332753],"genre_scores_gemma":[0.127013,0.06141125,0.1317495,0.001047681,0.04276403,0.0007342406,0.001116646,0.002486811,0.6316769],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4039764,"threshold_uncertainty_score":0.7583246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151905310595429,"score_gpt":0.2290300054594294,"score_spread":0.2175109523534751,"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."}}