{"id":"W4313638951","doi":"10.1139/as-2022-0031","title":"Surface-based temperature inversion characteristics and impact on surface air temperatures in northwestern Canada from radiosonde data between 1990 and 2016","year":2023,"lang":"en","type":"article","venue":"Arctic Science","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada; University of Lethbridge; Université Catholique de Louvain","keywords":"Radiosonde; Inversion (geology); Climatology; Beaufort sea; Surface air temperature; Arctic; Permafrost; Inversion temperature; Latitude; Environmental science; Geology; Lapse rate; Meteorology; Sea ice; Physical geography; Atmospheric sciences; Oceanography; Climate change; Geography; Geodesy; Geomorphology; Structural basin","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004998755,0.0001817239,0.0002134247,0.00009132708,0.0002945697,0.0001725855,0.0004586354,0.00005625001,0.0001399715],"category_scores_gemma":[0.0000824802,0.0001319976,0.00001199581,0.0007323719,0.0002550991,0.0004145225,0.00008456951,0.0002105872,0.0000235717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003039182,"about_ca_system_score_gemma":0.0005413014,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8086061,"about_ca_topic_score_gemma":0.7817348,"domain_scores_codex":[0.9983408,0.00005665757,0.0001649179,0.0005774013,0.0004368756,0.0004232999],"domain_scores_gemma":[0.9986171,0.0006022901,0.00005740635,0.0004228368,0.00003114991,0.0002692068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002390209,0.00000340392,0.9966164,0.00001423578,0.000003375623,0.00004898708,0.0002179067,0.0003021743,0.001512855,1.735675e-7,0.0008330157,0.0004235223],"study_design_scores_gemma":[0.0002567579,0.00005954096,0.9863346,0.0001004409,0.000007320232,0.000003468136,0.000190749,0.01244424,0.0001474773,0.00001061023,0.0002666807,0.0001781554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873459,0.0001927672,9.708176e-8,0.0009901359,0.0002531088,0.0001283186,0.01105354,0.00001978132,0.00001631455],"genre_scores_gemma":[0.9947073,0.000249725,0.00002969836,0.0005740667,0.00007370819,1.61082e-7,0.004336042,0.00000437488,0.00002492356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02687133,"threshold_uncertainty_score":0.5382704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03700836536505393,"score_gpt":0.2569142661123253,"score_spread":0.2199059007472714,"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."}}