{"id":"W3095107718","doi":"10.18280/ts.370408","title":"Recognition and Analysis of Behavior Features of School-Age Children Based on Video Image Processing","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Education Department of Shaanxi Province","keywords":"Optical flow; Computer science; Workflow; Frame (networking); Video processing; Artificial intelligence; Computer vision; Image processing; Artificial neural network; Dual (grammatical number); Image (mathematics); Pattern recognition (psychology); Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001541292,0.0001564165,0.0003411023,0.0002810329,0.00002927526,0.00002917114,0.00008433074,0.00005572376,0.0002053835],"category_scores_gemma":[0.00001785691,0.0001536368,0.0001119563,0.0005296885,0.00003778989,0.0001082316,0.000009119519,0.0001167641,0.000004201468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002828311,"about_ca_system_score_gemma":0.00001756177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000250053,"about_ca_topic_score_gemma":0.000008502355,"domain_scores_codex":[0.9989878,0.00004113168,0.0003566439,0.000189856,0.0002806842,0.0001438686],"domain_scores_gemma":[0.9996369,0.00003237168,0.00009463952,0.00009623278,0.00005535124,0.00008449275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000350603,0.0004354315,0.1092611,0.001680383,0.001419502,0.0000374667,0.001939236,0.04518504,0.7978999,0.00001004546,0.001222544,0.04055875],"study_design_scores_gemma":[0.001489121,0.0003554687,0.8251389,0.0002083495,0.00158406,0.000001261224,0.00009346996,0.07740159,0.09337644,0.000004819446,0.00001487203,0.0003316724],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937011,0.0001028567,0.005154226,0.00003734684,0.0000225549,0.0003353023,0.0002429243,0.00009302674,0.000310643],"genre_scores_gemma":[0.998504,0.00000231489,0.001069546,0.00005736919,0.00006316891,0.00002965214,0.0002476341,0.00002414731,0.00000213032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7158778,"threshold_uncertainty_score":0.6265126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801935327727814,"score_gpt":0.2232192696801525,"score_spread":0.2051999164028743,"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."}}