{"id":"W1592469096","doi":"10.3390/rs70709410","title":"Potential of C and X Band SAR for Shrub Growth Monitoring in Sub-Arctic Environments","year":2015,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Université du Québec à Trois-Rivières; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; Centre National de la Recherche Scientifique; ArcticNet","keywords":"Shrub; Tundra; Arctic; Vegetation (pathology); Arctic vegetation; Remote sensing; The arctic; Environmental science; Physical geography; Geology; Geography; Ecology; Oceanography; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000183077,0.00006930814,0.00011714,0.00005358619,0.00003536058,0.00001753379,0.00002885919,0.0000415293,0.000009444541],"category_scores_gemma":[0.0000316253,0.00006514219,0.00002001577,0.00005306435,0.00003460449,0.00008748585,0.000006420201,0.00004698395,0.000006488108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006392572,"about_ca_system_score_gemma":0.000008573967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002492726,"about_ca_topic_score_gemma":0.0007114973,"domain_scores_codex":[0.9994468,0.00002354912,0.0001233532,0.000129161,0.0001095698,0.0001675348],"domain_scores_gemma":[0.999759,0.00005329595,0.00003983894,0.00006100574,0.00001245852,0.00007444029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002629652,0.00001427206,0.7158695,0.0001982564,0.00002234379,0.00007612871,0.002074083,0.001364561,0.08959311,8.600202e-7,0.0000638623,0.19046],"study_design_scores_gemma":[0.002123449,0.0002693685,0.6428528,0.0003112411,0.00005080104,0.0001278268,0.00119015,0.3243597,0.0261023,0.001568427,0.0006415059,0.0004024879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998561,0.0006408053,0.0002277922,0.00006186741,0.0002025908,0.00009600569,0.00005496114,0.000003802194,0.0001511561],"genre_scores_gemma":[0.9985497,0.0002545311,0.0009432358,0.00001748027,0.000143011,1.383292e-9,0.00007420132,0.000003363821,0.00001447118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3229951,"threshold_uncertainty_score":0.3768272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04446454223424853,"score_gpt":0.2427005746492835,"score_spread":0.198236032415035,"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."}}