{"id":"W1994973996","doi":"10.5194/isprsarchives-xl-7-w3-1057-2015","title":"INTEGRATED SAR TECHNOLOGIES FOR MONITORING THE STABILITY OF MINE SITES: APPLICATION USING TERRASAR-X AND RADARSAT-2 IMAGES","year":2015,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Effigis (Canada)","funders":"Canadian Space Agency","keywords":"Permafrost; Terrain; Interferometric synthetic aperture radar; Geology; Remote sensing; Subsidence; Bedrock; Outcrop; Groundwater-related subsidence; Synthetic aperture radar; Mining engineering; Geomorphology; Cartography; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003739847,0.0004779728,0.0002337615,0.001366859,0.0001135624,0.0004882956,0.0003021965,0.0002946286,0.0007785744],"category_scores_gemma":[0.0002394514,0.0001878585,0.0001807744,0.00125302,0.000122903,0.0003377511,0.0003190846,0.0001791743,0.0003787293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002935891,"about_ca_system_score_gemma":0.000340276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005946493,"about_ca_topic_score_gemma":0.01332686,"domain_scores_codex":[0.9997829,0.0000347616,0.000009631412,0.00004704451,0.0001002231,0.00002549836],"domain_scores_gemma":[0.9998088,0.00001870751,0.00003436416,0.00001892046,0.0001012159,0.00001806696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005797964,0.0003169409,0.141657,0.0003661579,0.0002976634,0.0004312233,0.0004268665,0.02063277,0.35661,0.0004570111,0.002533975,0.4756905],"study_design_scores_gemma":[0.0001565012,0.0009325969,0.7018914,0.00008883523,0.0003470696,0.0009845687,0.001121379,0.2040266,0.08207017,0.0005592052,0.007739906,0.00008174666],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9012758,0.001364258,0.08520699,0.0001453365,0.00004899594,0.0002004639,0.001724557,0.00153319,0.008500442],"genre_scores_gemma":[0.901608,0.0007171846,0.09399688,0.00007894923,0.00002280017,0.0000673773,0.001305998,0.00003747169,0.002165314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005946493,"threshold_uncertainty_score":0.01182377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05283967766771078,"score_gpt":0.2793898978563064,"score_spread":0.2265502201885956,"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."}}