{"id":"W4327523052","doi":"10.1109/access.2023.3257280","title":"Video Relationship Detection Using Mixture of Experts","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Microsoft Research Asia; Microsoft Research; Microsoft","keywords":"Computer science; Artificial intelligence; Inference; Machine learning; Classifier (UML); Artificial neural network; Predicate (mathematical logic); Object detection; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001781903,0.00006871051,0.00008164948,0.0001919702,0.0001494361,0.00008977206,0.0006885718,0.00005731657,0.000004883622],"category_scores_gemma":[0.0001243796,0.00006831365,0.00003685938,0.001250039,0.00002065378,0.0005210515,0.0001271227,0.0001081511,0.00003775195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002719995,"about_ca_system_score_gemma":0.00002541851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004956007,"about_ca_topic_score_gemma":0.00002252761,"domain_scores_codex":[0.9992489,0.00005978752,0.0001638333,0.0002255887,0.0001712572,0.0001306347],"domain_scores_gemma":[0.9991317,0.0002074639,0.0001038931,0.0004513825,0.00006751782,0.00003805177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001589713,0.0001352364,0.3500945,0.0001315566,0.0000461608,0.0000129988,0.004364379,0.2334129,0.2908529,0.01249428,0.001540611,0.1068985],"study_design_scores_gemma":[0.0001183192,0.000009836584,0.3052832,0.00001789457,0.000004456543,0.00000563513,0.00001011562,0.6556563,0.03405059,0.004491494,0.0002410957,0.0001110581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5939758,0.000008963502,0.4051058,0.0002466688,0.0002011841,0.00007917988,6.465899e-7,0.000214179,0.0001675136],"genre_scores_gemma":[0.9939139,0.000001443321,0.005887517,0.00005078468,0.00006730707,0.00002551404,0.000001488662,0.000008798816,0.00004324809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4222434,"threshold_uncertainty_score":0.278575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07794275924308183,"score_gpt":0.3754505869616347,"score_spread":0.2975078277185529,"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."}}