{"id":"W2033218924","doi":"10.5589/m07-006","title":"Towards traffic monitoring with TerraSAR-X","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Synthetic aperture radar; Context (archaeology); Aerospace; Computer science; A priori and a posteriori; Remote sensing; Radar; Geography; Real-time computing; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.000246016,0.0001161691,0.0001558912,0.0002581294,0.0000805824,0.00003659697,0.00009772136,0.0000714028,0.000006421295],"category_scores_gemma":[0.00001834843,0.0001007587,0.00004984529,0.0001901244,0.00004333664,0.00006295092,0.000002060511,0.0002385803,0.000001837813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002358464,"about_ca_system_score_gemma":0.0001802872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000781441,"about_ca_topic_score_gemma":0.003242885,"domain_scores_codex":[0.9992927,0.000006080876,0.0002327275,0.00006857951,0.0001182029,0.0002817282],"domain_scores_gemma":[0.9993177,0.00002710529,0.0000563678,0.0001399908,0.00009817602,0.0003606253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002113702,5.803216e-7,0.00003069297,0.000006101317,0.00002082262,0.0001807803,0.0002731168,0.00002761459,0.0002286036,0.000008361574,0.0001256853,0.9990955],"study_design_scores_gemma":[0.0002996319,0.0000963303,0.002375121,0.0006069939,0.00006359041,0.004373468,0.000852347,0.009993015,0.0579058,0.0002048302,0.9228059,0.0004229506],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.236545,0.0004873986,0.757736,0.0001497034,0.0002484165,0.00005129826,7.866056e-7,0.0000556093,0.004725803],"genre_scores_gemma":[0.5199244,0.00001213667,0.4798284,0.00001354983,0.0001921033,3.402251e-9,1.756919e-7,0.00002043386,0.000008737596],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9986726,"threshold_uncertainty_score":0.4108819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01033957471734668,"score_gpt":0.2165446483301179,"score_spread":0.2062050736127712,"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."}}