{"id":"W3112388675","doi":"10.4095/327790","title":"The Government of Canada automated processing system for change detection and ground deformation analysis from RADARSAT-2 and RADARSAT Constellation Mission Synthetic Aperture Radar data: description and user guide","year":2020,"lang":"en","type":"report","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Synthetic aperture radar; Constellation; Remote sensing; Deformation monitoring; Interferometric synthetic aperture radar; Inverse synthetic aperture radar; Radar imaging; Data processing; Radar; Computer science; Geology; Geography; Telecommunications; Meteorology; Deformation (meteorology); Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001754485,0.001771802,0.0007577835,0.004737648,0.002116418,0.00316235,0.002155548,0.0008608917,0.06516563],"category_scores_gemma":[0.003139009,0.0007945146,0.0004312239,0.00707736,0.0007829872,0.00119733,0.0008325712,0.0009716331,0.07016267],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01329874,"about_ca_system_score_gemma":0.05804432,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8513879,"about_ca_topic_score_gemma":0.8690928,"domain_scores_codex":[0.9958639,0.000145541,0.00008331218,0.0002293725,0.003346462,0.0003312885],"domain_scores_gemma":[0.9893854,0.0003122461,0.0001690307,0.0005288204,0.009218462,0.0003860718],"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":[0.00008794793,0.0001182676,0.001452698,0.0002569018,0.00001457259,0.00008061648,0.000119052,0.002780909,0.005953946,0.004722721,0.7399564,0.2444559],"study_design_scores_gemma":[0.00002797627,0.00003067369,0.00367126,0.00008887364,0.000009981583,0.00006564903,0.00008338108,0.00474452,0.004025764,0.0004990944,0.986707,0.00004576752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007068028,0.002490269,0.1592528,0.002100921,0.0006735849,0.004184315,0.2646448,0.04510575,0.5144796],"genre_scores_gemma":[0.01719778,0.00487915,0.2014071,0.0007029481,0.0001094955,0.001819096,0.2570132,0.007571569,0.5092998],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9867013,"threshold_uncertainty_score":0.2989746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02724773963314416,"score_gpt":0.2412635353494334,"score_spread":0.2140157957162892,"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."}}