{"id":"W4400202461","doi":"10.1080/01431161.2024.2367172","title":"Automatic detection and tracking polar lows from synthetic aperture radar and radiometer observations","year":2024,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"National Natural Science Foundation of China","keywords":"Remote sensing; Synthetic aperture radar; Geology; Tracking (education); Radiometer; Polar; Radar; Geodesy; Computer science; Telecommunications; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001378868,0.00009895463,0.0001293281,0.00007522496,0.00005457508,0.0002536321,0.00006172628,0.00003547909,0.00005153953],"category_scores_gemma":[0.00003336432,0.000086822,0.00007337299,0.0000712737,0.00002832608,0.0003146226,0.00002386837,0.0002031186,0.00000234881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003995849,"about_ca_system_score_gemma":0.00003448744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002639524,"about_ca_topic_score_gemma":0.00002280504,"domain_scores_codex":[0.999332,0.00003576315,0.0002542557,0.000112459,0.0001813088,0.00008424716],"domain_scores_gemma":[0.9994043,0.0002566586,0.00011341,0.00005174864,0.0001257072,0.00004815151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001166836,0.000005924519,0.0001105239,0.000007256808,0.0002159454,0.00003815287,0.0003658376,0.0000204081,0.01804078,0.0001323288,0.00002800404,0.9810232],"study_design_scores_gemma":[0.0004656453,0.00005591987,0.00388872,0.0006612931,0.0001511912,0.000360872,0.000505325,0.9661355,0.00128869,0.01258375,0.01369654,0.0002065477],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.779274,0.0007409766,0.21798,0.0007458363,0.001011437,0.0000366449,0.00001368275,0.00001553285,0.0001818928],"genre_scores_gemma":[0.9596738,0.0000347606,0.0395042,0.00008885028,0.0006277473,1.647973e-8,0.000007196417,0.00001554677,0.00004795374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9808166,"threshold_uncertainty_score":0.3540499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009075548433191982,"score_gpt":0.2312801820851812,"score_spread":0.2222046336519893,"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."}}