{"id":"W2094929092","doi":"10.1049/iet-rsn:20060113","title":"Design and experimental validation of knowledge-based constant false alarm rate detectors","year":2007,"lang":"en","type":"article","venue":"IET Radar Sonar & Navigation","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University","keywords":"Constant false alarm rate; A priori and a posteriori; Detector; Computer science; Radar; False alarm; Constant (computer programming); ALARM; Real-time computing; Artificial intelligence; Data mining; Pattern recognition (psychology); Algorithm; Engineering; Telecommunications; Electrical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007001266,0.0001419053,0.0001705769,0.00008072378,0.00007825936,0.00003112389,0.00005209281,0.00008608921,0.000008654698],"category_scores_gemma":[0.000008450065,0.0001451019,0.00003275568,0.0001744176,0.00005152342,0.0001755908,0.000006614327,0.00008555961,0.000004693738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009081364,"about_ca_system_score_gemma":0.00003602901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000151942,"about_ca_topic_score_gemma":0.000001696272,"domain_scores_codex":[0.9991422,0.00006173662,0.000335346,0.0001469856,0.0001475372,0.0001662196],"domain_scores_gemma":[0.9995792,0.0001178843,0.00008499515,0.00008924754,0.00006237108,0.00006632058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005344964,0.00003370475,0.0002641507,0.0001552016,0.00002132935,0.00000855195,0.001122647,0.009018767,0.9800225,0.00006063332,0.00007193235,0.009167082],"study_design_scores_gemma":[0.000543882,0.00007174458,0.0001989783,0.0001717519,0.00001205323,0.000008561789,0.0002531756,0.03001046,0.9681106,0.00007081326,0.0003906476,0.0001573682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7488259,0.001779441,0.248741,0.000006106107,0.0001511654,0.000212558,0.000003292073,0.00009371831,0.0001867918],"genre_scores_gemma":[0.9934085,0.000004358563,0.006473142,0.000005726009,0.00004641731,0.000006263933,0.00001872026,0.0000281193,0.000008768143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2445826,"threshold_uncertainty_score":0.5917085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541998279851114,"score_gpt":0.2495666121335564,"score_spread":0.2341466293350452,"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."}}