{"id":"W2981846602","doi":"10.4095/220730","title":"Terrain image maps from SAR fusion techniques","year":2003,"lang":"en","type":"report","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Terrain; Remote sensing; Image fusion; Image (mathematics); Geology; Fusion; Computer vision; Computer science; Cartography; Artificial intelligence; Computer graphics (images); Geography","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":[0.0002659796,0.0004707229,0.0002702443,0.002208957,0.0002351226,0.000717272,0.0002971389,0.000276909,0.003855397],"category_scores_gemma":[0.0007760673,0.0002244172,0.000443323,0.002308179,0.0001667292,0.0007872341,0.0006733916,0.000326592,0.001795947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002864453,"about_ca_system_score_gemma":0.0003074205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002204098,"about_ca_topic_score_gemma":0.00360186,"domain_scores_codex":[0.9997111,0.00002334578,0.00001031388,0.00003793856,0.0001812896,0.0000359105],"domain_scores_gemma":[0.999787,0.00002449452,0.00001768317,0.00004754645,0.0001161208,0.000007189093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000322434,0.00005800997,0.005248042,0.0002911401,0.0001382075,0.0003719207,0.0002319852,0.06620258,0.130194,0.006250123,0.00728965,0.7834019],"study_design_scores_gemma":[0.0001698153,0.0003593502,0.09285189,0.0001702909,0.0004259338,0.001761801,0.0005633034,0.4869391,0.3019329,0.02328284,0.09136364,0.0001791408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2707124,0.001540474,0.6510009,0.0004968531,0.0002432711,0.0002736467,0.005845866,0.007756174,0.06213045],"genre_scores_gemma":[0.6252682,0.001434674,0.3553336,0.00008939782,0.00007568999,0.00009957376,0.009635484,0.0005128733,0.007550521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003855397,"threshold_uncertainty_score":0.01289761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129735950185515,"score_gpt":0.2495409569719607,"score_spread":0.2382435974701056,"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."}}