{"id":"W4285043601","doi":"10.36227/techrxiv.20270298.v1","title":"A novel back-projection algorithm based on time-delay evaluated by 2-D CFAR","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Clutter; Computer science; Algorithm; Radar; Antenna (radio); Artificial intelligence; Projection (relational algebra); Feature (linguistics); Noise (video); Back projection; Computer vision; Image (mathematics); Telecommunications","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005195389,0.0004834971,0.0004750229,0.0004331355,0.0001124534,0.0001403618,0.0003664219,0.0002181293,0.009081501],"category_scores_gemma":[0.00001755492,0.0005059043,0.0003144621,0.0003573897,0.00002432059,0.00003422023,0.0001943532,0.001048361,0.0006969835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004836498,"about_ca_system_score_gemma":0.00006457926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006072434,"about_ca_topic_score_gemma":0.00000397302,"domain_scores_codex":[0.9979688,0.00009181585,0.0004107778,0.0006721482,0.0004837406,0.0003727267],"domain_scores_gemma":[0.9988791,0.00005748983,0.00007775707,0.0008257684,0.00006094521,0.00009896059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006999761,0.00009599749,0.000009534237,0.0001070129,0.0002716109,0.000004774171,0.00005352186,0.8283077,0.02258278,3.699134e-7,0.1354859,0.01307386],"study_design_scores_gemma":[0.0003553719,0.00003329527,0.00001096939,0.00005869389,0.0001384585,0.000006441517,0.00001471371,0.9767291,0.002655863,0.000007435416,0.01943695,0.0005526863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003262079,0.0002495977,0.9544067,0.0004719195,0.001308003,0.0005197502,0.0007069805,0.002185294,0.03688961],"genre_scores_gemma":[0.3679585,0.0005468294,0.367875,0.00605337,0.002202178,0.002280627,0.03035056,0.002847747,0.2198852],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5865318,"threshold_uncertainty_score":0.9997392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127486066547295,"score_gpt":0.2356135766969898,"score_spread":0.2228649700422604,"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."}}