{"id":"W1974419126","doi":"10.3390/rs6098565","title":"Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada","year":2014,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Elitenetzwerk Bayern; National Wildlife Research Center; Bayerische Forschungsallianz","keywords":"Tundra; Remote sensing; Synthetic aperture radar; Land cover; Multispectral image; Polarimetry; Multispectral pattern recognition; Radar; Contextual image classification; Geology; Scattering; Arctic; Computer science; Artificial intelligence; Land use; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001238362,0.0001086798,0.0002049626,0.00003566167,0.00007581186,0.00002676967,0.00002326416,0.00005720211,0.00004445939],"category_scores_gemma":[0.00004403546,0.00009226718,0.00001264948,0.000043556,0.000104905,0.0000898147,0.000006226747,0.00006677794,7.952835e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000694951,"about_ca_system_score_gemma":0.00001575118,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0904047,"about_ca_topic_score_gemma":0.159448,"domain_scores_codex":[0.9993072,0.00006865912,0.0001652105,0.0001777976,0.0001435878,0.0001375208],"domain_scores_gemma":[0.9995334,0.0001770755,0.0001165738,0.00009175976,0.00001218949,0.00006899609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007500797,0.000004954312,0.2051871,0.0001379548,0.0000199484,0.000002779425,0.0004425927,0.000002802052,0.7763908,6.819985e-7,0.00002568846,0.01770968],"study_design_scores_gemma":[0.0009459814,0.00007375617,0.7835507,0.000139935,0.00006549578,0.00008563728,0.00009079399,0.2088124,0.003272469,0.00002501891,0.002713934,0.0002237847],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966135,0.0003757698,0.00150992,0.0003030746,0.00005624413,0.00009802474,0.0009388761,0.000003239712,0.0001013537],"genre_scores_gemma":[0.9981626,0.0005550251,0.0001222655,0.0001037637,0.00003059912,4.915848e-9,0.0009624543,0.00000486587,0.0000583774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7731183,"threshold_uncertainty_score":0.9156524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009146187722649845,"score_gpt":0.184818348864747,"score_spread":0.1756721611420971,"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."}}