{"id":"W3173064455","doi":"10.5194/egusphere-egu21-14864","title":"SMART &amp;#8211; Space monitoring of Arctic Tundra landscapes","year":2021,"lang":"en","type":"article","venue":"","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Permafrost; Tundra; Remote sensing; Arctic; Land cover; Ground truth; Satellite; Environmental science; Geography; Geology; Land use; Oceanography; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002052469,0.0002552329,0.0001532996,0.0009765439,0.0002835117,0.0004335362,0.0002998838,0.0001586483,0.001152765],"category_scores_gemma":[0.0001847203,0.00008239243,0.000139017,0.0008754151,0.000173347,0.0002524208,0.0004383547,0.0001128302,0.0002893316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003414215,"about_ca_system_score_gemma":0.0003269693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03027709,"about_ca_topic_score_gemma":0.07217447,"domain_scores_codex":[0.9998623,0.00001911257,0.000004896153,0.00004253618,0.0000456553,0.00002547506],"domain_scores_gemma":[0.9998537,0.000007998099,0.0000241524,0.00002284591,0.00005871113,0.00003250011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006951206,0.0003155079,0.489608,0.0003579478,0.0002389416,0.0008847042,0.001476978,0.04035758,0.2192173,0.001785075,0.009667924,0.2353949],"study_design_scores_gemma":[0.00004569728,0.0001981625,0.9035527,0.0000607252,0.00006242511,0.0002098424,0.0008065604,0.04490328,0.0236037,0.000435472,0.02608765,0.00003398678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725065,0.0003085094,0.005281527,0.00008474661,0.0000217262,0.00007133896,0.007888308,0.0004449665,0.01339232],"genre_scores_gemma":[0.977562,0.0002686305,0.01153714,0.00005278174,0.0000285464,0.00006120728,0.007449477,0.00006558953,0.00297462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03027709,"threshold_uncertainty_score":0.06020176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05100299193227767,"score_gpt":0.2546958742200152,"score_spread":0.2036928822877375,"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."}}