{"id":"W237164291","doi":"10.21236/ada387790","title":"An Algorithm-Level Test Bed for Level-One Data Fusion Research (CASE-ATTI)","year":2001,"lang":"en","type":"report","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Test (biology); Computer science; Algorithm; Sensor fusion; Fusion; Data mining; Artificial intelligence; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.007972446,0.0006659366,0.0009037902,0.0007552719,0.001531576,0.001313499,0.008427099,0.001096937,0.0003798337],"category_scores_gemma":[0.001980165,0.0006025615,0.0001446153,0.001469907,0.000175677,0.001355367,0.004759159,0.001764416,0.0001410151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002654998,"about_ca_system_score_gemma":0.001532215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004775446,"about_ca_topic_score_gemma":0.001800565,"domain_scores_codex":[0.9900934,0.0003607112,0.001220225,0.003303121,0.003440745,0.001581763],"domain_scores_gemma":[0.9830608,0.003298253,0.0004215966,0.009734016,0.002868362,0.0006169705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006685789,0.0005906924,0.00002748403,0.00007478905,0.00003343018,0.0008253345,0.00005738312,0.00001626676,0.00004250016,0.0001689393,0.5020167,0.4961397],"study_design_scores_gemma":[0.0006286833,0.0006937193,0.0001300242,0.0003886029,0.00004905882,0.00411533,0.0001069479,0.2479531,0.00007988275,0.0006511199,0.7442045,0.0009990098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007909548,0.0006418143,0.9744861,0.0005527925,0.003594817,0.001375493,0.006851041,0.0008110691,0.01160783],"genre_scores_gemma":[0.001607485,0.003937035,0.9412054,0.0002249935,0.005913017,0.0001473136,0.01513699,0.0001933159,0.03163438],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4951407,"threshold_uncertainty_score":0.9997683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5805420958756612,"score_gpt":0.4659472866285845,"score_spread":0.1145948092470767,"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."}}