{"id":"W2167012024","doi":"10.1023/a:1015416203917","title":"Parameter Estimation and the CRLB with Uncertain Origin Measurements","year":2001,"lang":"en","type":"article","venue":"Methodology And Computing In Applied Probability","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Air Force Office of Scientific Research; Office of Naval Research","keywords":"Cramér–Rao bound; Upper and lower bounds; Mathematics; Algorithm; Statistics; Reduction (mathematics); Estimation theory; Scalar (mathematics); Uncertainty reduction theory; Focus (optics); Data mining; Computer science","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":[0.006464656,0.0001507471,0.0002876658,0.00004646404,0.0002300753,0.00008715399,0.0003076906,0.00009636368,0.000002626439],"category_scores_gemma":[0.0003068833,0.00009368361,0.00001716814,0.0003022845,0.0004052427,0.00006583892,0.0002160827,0.0002989288,0.000001406875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002125718,"about_ca_system_score_gemma":0.00002231886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007405333,"about_ca_topic_score_gemma":0.00003084744,"domain_scores_codex":[0.9975497,0.001198563,0.0002892368,0.0005401908,0.0001544002,0.0002679707],"domain_scores_gemma":[0.9961944,0.003173548,0.0001089652,0.0004431733,0.00003310512,0.00004685355],"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":[0.0007311711,0.0001041238,0.09853864,0.00005671316,0.00003602524,0.000008045723,0.002366548,0.04085403,0.00005317971,0.2240868,0.00004099443,0.6331238],"study_design_scores_gemma":[0.00234724,0.00006649198,0.05007927,0.00003527785,0.00001675334,0.0001037332,0.00004083252,0.6078014,0.00008507952,0.3388344,0.0003470398,0.00024248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2986077,0.00008673315,0.6999564,0.0004911426,0.00008078273,0.0002967329,2.056369e-7,0.0000661618,0.000414181],"genre_scores_gemma":[0.5085764,0.000006844841,0.4911571,0.000225087,0.00001406521,0.00001379576,0.000001067147,0.000002761043,0.000002831045],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6328812,"threshold_uncertainty_score":0.3820307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.146552179225459,"score_gpt":0.325298180941565,"score_spread":0.178746001716106,"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."}}