{"id":"W4407162165","doi":"10.1190/4d-forum2024-030.1","title":"Quantification of 4D signal and generating density change maps: An East Coast Canada case study","year":2025,"lang":"en","type":"article","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"East coast; SIGNAL (programming language); Computer science; Geography; Remote sensing; Physical geography","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":[0.001065033,0.0006848997,0.0003761617,0.00439697,0.001167944,0.001868796,0.001199543,0.0006054588,0.002473016],"category_scores_gemma":[0.003944712,0.0003605681,0.0004803771,0.007053772,0.0009472783,0.0005728938,0.001294757,0.0006772646,0.0003874447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00968945,"about_ca_system_score_gemma":0.005492764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8716807,"about_ca_topic_score_gemma":0.8953696,"domain_scores_codex":[0.9988788,0.00008619441,0.00004267173,0.0001304918,0.0006980879,0.0001637065],"domain_scores_gemma":[0.9977546,0.0003883237,0.0001161509,0.0001957204,0.001461209,0.0000839443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004126203,0.0003955553,0.2192723,0.0005486065,0.0002480374,0.003176732,0.004294884,0.3931565,0.01754702,0.01873912,0.01320737,0.3290011],"study_design_scores_gemma":[0.00006196273,0.000116274,0.2448422,0.000206406,0.0001112722,0.0007487598,0.006634467,0.6732326,0.02105644,0.005453454,0.04726819,0.0002678351],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8782493,0.0004716772,0.06781867,0.001073017,0.00006611327,0.0005001577,0.01870834,0.002006231,0.03110653],"genre_scores_gemma":[0.9106908,0.0002256471,0.0801075,0.00005691651,0.00001114144,0.00008862759,0.005425542,0.0002457758,0.003147962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1283193,"threshold_uncertainty_score":0.2581499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024819729736649,"score_gpt":0.2246488950104948,"score_spread":0.2044006977131284,"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."}}