{"id":"W3009779811","doi":"10.1109/wacv45572.2020.9093481","title":"Few-Shot Learning of Video Action Recognition Only Based on Video Contents","year":2020,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Frame (networking); Action recognition; Feature extraction; Class (philosophy); Training set; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001310734,0.0001146949,0.0001454631,0.0001173485,0.0001086416,0.00007637626,0.000182095,0.00006360648,0.0005538138],"category_scores_gemma":[0.0001366446,0.0001100527,0.00008965044,0.0002814083,0.00001788571,0.0005338287,0.00003264349,0.0002014772,0.000575592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002898379,"about_ca_system_score_gemma":0.00003839871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002592956,"about_ca_topic_score_gemma":0.000007040086,"domain_scores_codex":[0.9988807,0.0001126353,0.0002517087,0.000320271,0.0002864716,0.0001481794],"domain_scores_gemma":[0.9993319,0.0001138059,0.0001598626,0.0001405134,0.0001501071,0.0001038386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003532754,0.0004816918,0.001683844,0.0001601184,0.00006441303,0.00002059313,0.0008549519,0.00199708,0.06843189,0.002491311,0.006925201,0.9165356],"study_design_scores_gemma":[0.00264389,0.001879269,0.006059361,0.0002201073,0.00003462116,0.00001067422,0.000321204,0.7215429,0.2540371,0.001133305,0.01156767,0.0005498905],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2487795,0.000006716209,0.7107459,0.003782905,0.0004291213,0.0003113685,0.000006138524,0.0005590611,0.03537923],"genre_scores_gemma":[0.9937287,0.000007569604,0.002793552,0.003075066,0.00009592957,0.000008167061,0.00003216027,0.000008871421,0.0002500123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9159858,"threshold_uncertainty_score":0.7398263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1106315303825953,"score_gpt":0.2855607421283969,"score_spread":0.1749292117458016,"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."}}