{"id":"W6925180666","doi":"10.1594/pangaea.894755","title":"Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Datasets","year":2018,"lang":"en","type":"other","venue":"Publishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)","topic":"Physics and Engineering Research Articles","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Seventh Framework Programme","keywords":"Permafrost; Transect; Geospatial analysis; Arctic; Thermokarst; Abundance (ecology); Tundra; Spatial distribution","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":[0.0004692254,0.0004970192,0.0001948787,0.002497884,0.0002462268,0.0004646564,0.0003451285,0.0002369367,0.003770612],"category_scores_gemma":[0.001087183,0.000182235,0.0002740371,0.00331487,0.0001409352,0.00039399,0.0004805037,0.000237155,0.001873442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005763018,"about_ca_system_score_gemma":0.0007666707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07056253,"about_ca_topic_score_gemma":0.1128627,"domain_scores_codex":[0.9996933,0.00003047397,0.00003126968,0.0001012263,0.0001058184,0.00003802434],"domain_scores_gemma":[0.9991648,0.00008366465,0.0002042178,0.0001235645,0.0003608071,0.00006296852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003191097,0.0003579003,0.5225345,0.0007727388,0.0004750306,0.0001710928,0.0007198522,0.01048171,0.006992554,0.002300449,0.3605761,0.09429906],"study_design_scores_gemma":[0.00004261761,0.00002685699,0.8587356,0.00008295065,0.00005071876,0.00008034489,0.0003723735,0.003783962,0.002456349,0.0004393223,0.1338995,0.00002929211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.09866157,0.0001933649,0.001088357,0.0001005644,0.00002523391,0.00005249062,0.8930005,0.0004349694,0.006442889],"genre_scores_gemma":[0.07638816,0.0001691043,0.004427549,0.0000425797,0.00002126719,0.0001512405,0.9160008,0.00007712219,0.002722135],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07056253,"threshold_uncertainty_score":0.1403037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04567146326969568,"score_gpt":0.2782830874147862,"score_spread":0.2326116241450906,"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."}}