{"id":"W2944346567","doi":"10.35298/pkc.2018.07","title":"Pushing remote sensing capacity for climate change research in Canada’s North: POLAR’s contributions to NASA's Arctic-Boreal Vulnerability Experiment (ABoVE)","year":2019,"lang":"en","type":"article","venue":"Polar Knowledge Aqhaliat Report","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Vulnerability (computing); Boreal; Arctic; Environmental science; Polar; Climatology; The arctic; Cold climate; Remote sensing; Geography; Meteorology; Physical geography; Oceanography; Geology; Computer science; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.01291038,0.000658171,0.0004703707,0.001579811,0.006554772,0.00732379,0.001776087,0.002216194,0.006903223],"category_scores_gemma":[0.01997861,0.0003913407,0.0005852878,0.002545769,0.004346782,0.005023099,0.005659906,0.004449922,0.0007156071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02087603,"about_ca_system_score_gemma":0.1448283,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9732828,"about_ca_topic_score_gemma":0.9854946,"domain_scores_codex":[0.9963446,0.0005972118,0.00007273204,0.0002993062,0.001703711,0.0009824699],"domain_scores_gemma":[0.9695413,0.008766796,0.0004234664,0.001322434,0.01338409,0.006561867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003538181,0.0001774488,0.03644794,0.000446353,0.0002112362,0.0002496238,0.004490822,0.003688776,0.004564532,0.06057828,0.696944,0.1918472],"study_design_scores_gemma":[0.0001912668,0.00005763687,0.06150511,0.0009226368,0.000150658,0.00009775056,0.01136473,0.004713777,0.002990545,0.04572827,0.8720448,0.0002328006],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.06843467,0.02090413,0.005717062,0.812762,0.004299213,0.0001321716,0.008225789,0.0005149947,0.07901002],"genre_scores_gemma":[0.7395825,0.03900252,0.05496934,0.1133658,0.003690943,0.0003154086,0.008129078,0.0005361082,0.04040824],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02671725,"threshold_uncertainty_score":0.151467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04696088096121032,"score_gpt":0.3246086738628875,"score_spread":0.2776477929016772,"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."}}