{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002459243,0.0001554064,0.0001359738,0.00008764531,0.0005547773,0.001564632,0.00107315,0.00007656037,0.0003879988],"category_scores_gemma":[0.0002486869,0.000149037,0.0000316035,0.00003629941,0.0002085411,0.0004470165,0.0002496532,0.0001551988,0.00016457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002296505,"about_ca_system_score_gemma":0.00004557186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000710976,"about_ca_topic_score_gemma":0.00004578879,"domain_scores_codex":[0.9986157,0.00005745664,0.0003133613,0.0004152373,0.0003836744,0.0002145505],"domain_scores_gemma":[0.9986612,0.0001681282,0.0001749668,0.0005614351,0.0003232667,0.0001110202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003780921,0.00004089972,0.00007856797,0.000002612279,0.00001182979,0.00004152749,0.0001460819,0.00009399719,0.0005997788,0.8055378,0.0004959137,0.1929131],"study_design_scores_gemma":[0.00006769678,0.0001401255,0.001182287,0.00006077803,0.000007534975,0.00002793163,0.0001562643,0.6227185,0.003275033,0.3704912,0.001578237,0.0002944677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003093569,0.000007011815,0.9822624,0.003053244,0.00184893,0.00008903315,0.0002143326,0.00007392597,0.00935754],"genre_scores_gemma":[0.9371673,0.0001720632,0.06165456,0.0003694067,0.0002756173,0.000006553667,0.0000590644,0.000007810241,0.0002876462],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9340737,"threshold_uncertainty_score":0.9994718,"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."}}