{"id":"W2644693190","doi":"","title":"Unsupervised Sequential Sensor Acquisition","year":2017,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005579607,0.0008326934,0.0008045738,0.0005899216,0.0003765201,0.0008355551,0.0005712144,0.0005450316,0.003631985],"category_scores_gemma":[0.001272139,0.0005494116,0.0005469413,0.0008453747,0.0005590434,0.001096594,0.0009942818,0.0008078807,0.001541184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003595364,"about_ca_system_score_gemma":0.001149396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002897127,"about_ca_topic_score_gemma":0.00612811,"domain_scores_codex":[0.9995446,0.00006492124,0.00002420674,0.0001681475,0.0001597331,0.00003842028],"domain_scores_gemma":[0.9994313,0.0001242719,0.00004031436,0.0002055352,0.0001731665,0.00002551116],"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":[0.0003895588,0.0001355951,0.001760054,0.0001505688,0.0001143684,0.0001270167,0.00009419191,0.08456396,0.07550633,0.01602072,0.01002632,0.8111114],"study_design_scores_gemma":[0.00001645933,0.0000845925,0.003434924,0.0000157531,0.00003385289,0.0002549393,0.00002603962,0.9379231,0.03053954,0.01035136,0.01729348,0.0000259112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01074371,0.0004131798,0.9836135,0.0001454084,0.0001839306,0.00004741931,0.0002182857,0.0007290904,0.003905462],"genre_scores_gemma":[0.4064335,0.001202963,0.5592855,0.0002179133,0.0002879016,0.0001540891,0.002079406,0.0002767041,0.03006205],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003631985,"threshold_uncertainty_score":0.01215017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1415958106355498,"score_gpt":0.3586155390995791,"score_spread":0.2170197284640293,"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."}}