{"id":"W2789011059","doi":"10.1109/cvpr.2018.00056","title":"Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points","year":2018,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Feature (linguistics); Artificial intelligence; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001055368,0.0001526219,0.0001332633,0.00009167348,0.0003233583,0.0002222565,0.0003462806,0.0001375316,0.0013288],"category_scores_gemma":[0.00001985855,0.000135321,0.00007135412,0.0002275183,0.00006394152,0.0008259536,0.00009867958,0.0001888986,0.001175244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004135829,"about_ca_system_score_gemma":0.00002293102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000148638,"about_ca_topic_score_gemma":0.0002470269,"domain_scores_codex":[0.9989147,0.00008694457,0.000124636,0.0004386977,0.0002132525,0.0002217536],"domain_scores_gemma":[0.9992027,0.00003607759,0.00009833246,0.0004033979,0.0001565041,0.0001029841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004751368,0.0001908709,0.0003168462,0.000009500156,0.00007968891,0.0000185537,0.0009931269,1.640944e-7,0.1356058,0.003184316,0.03423822,0.8253154],"study_design_scores_gemma":[0.00151005,0.0004050647,0.04928134,0.00006947232,0.00003379567,0.00003700558,0.00006873659,0.002775783,0.7186894,0.2136914,0.01267829,0.0007596015],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9054973,0.000005504704,0.07548713,0.0009888684,0.0008452235,0.0001401054,0.00002196399,0.0004506041,0.01656327],"genre_scores_gemma":[0.9831643,0.000002819363,0.01427161,0.00101471,0.0008035742,0.00000689558,0.00005045192,0.000009747902,0.000675861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8245558,"threshold_uncertainty_score":0.9996024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02532363964492933,"score_gpt":0.2646313111674463,"score_spread":0.239307671522517,"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."}}