{"id":"W4408044438","doi":"10.1007/978-981-96-2186-6_16","title":"Lightweight and Efficient Top-Down Human Pose Estimation Algorithm Research","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital","funders":"","keywords":"Computer science; Estimation; Algorithm; Artificial intelligence; Engineering; Systems engineering","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":[0.0008374925,0.002129266,0.002007742,0.001268289,0.0007253036,0.001958892,0.002902726,0.001252521,0.01999597],"category_scores_gemma":[0.002296956,0.001024664,0.00144139,0.001936961,0.0005164327,0.003098841,0.002185669,0.001833894,0.02047414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005849807,"about_ca_system_score_gemma":0.001422259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003644006,"about_ca_topic_score_gemma":0.005425829,"domain_scores_codex":[0.9986581,0.0001447744,0.00006127724,0.0003647936,0.0006542563,0.0001167219],"domain_scores_gemma":[0.9987679,0.0002691714,0.00004756198,0.00047246,0.0003962423,0.0000467884],"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":[0.0001482092,0.0001011443,0.0003154791,0.0001596767,0.00007555463,0.0000572709,0.00003655235,0.01865114,0.0409926,0.007453682,0.01348728,0.9185214],"study_design_scores_gemma":[0.0000330091,0.0002551043,0.001214263,0.00005473489,0.00008958644,0.000445517,0.00006679381,0.835545,0.08535914,0.03190075,0.04497006,0.00006611116],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001428765,0.0004876486,0.9937068,0.00005530504,0.00009434019,0.00004419313,0.0001140159,0.002185764,0.001883293],"genre_scores_gemma":[0.03687321,0.001551413,0.939514,0.0002080173,0.0002134743,0.0001503841,0.001727295,0.0008600756,0.01890219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01999597,"threshold_uncertainty_score":0.06689316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05412926551910804,"score_gpt":0.3569906034859194,"score_spread":0.3028613379668114,"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."}}