{"id":"W4411717561","doi":"10.31223/x5d15c","title":"Multi-component Rayleigh wave dispersion analysis for Vs-depth profiling of Glaciers","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glacier; Profiling (computer programming); Dispersion (optics); Rayleigh scattering; Rayleigh wave; Geology; Surface wave; Geomorphology; Optics; Computer science; Physics","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":[0.0007119003,0.0006141888,0.0002569258,0.001373521,0.0002638102,0.0005856094,0.0004524079,0.0003759312,0.0007243932],"category_scores_gemma":[0.002582015,0.0002382574,0.0003197701,0.0007647772,0.0002339363,0.000651488,0.0004974465,0.0005838909,0.0003180523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005173179,"about_ca_system_score_gemma":0.0007867998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01621214,"about_ca_topic_score_gemma":0.03348204,"domain_scores_codex":[0.9997786,0.00005725955,0.00001159192,0.00004922787,0.00007049463,0.00003296102],"domain_scores_gemma":[0.9993145,0.0002633154,0.00007459493,0.0001219166,0.0001818543,0.0000437191],"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":[0.0002105535,0.00018021,0.02857866,0.00005898947,0.00009068818,0.00007735355,0.0002309562,0.5498152,0.03884861,0.002611961,0.00219293,0.3771039],"study_design_scores_gemma":[0.000004508481,0.00001412787,0.005367476,0.000004377757,0.000005550441,0.00001408587,0.0000433737,0.9889711,0.003845979,0.001242813,0.0004779048,0.000008741535],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4287513,0.0002323171,0.5661938,0.0002913642,0.00002514495,0.0000389232,0.0007350288,0.001994235,0.001737881],"genre_scores_gemma":[0.8137718,0.000136153,0.183322,0.0000377568,0.00002139592,0.00002680733,0.001390936,0.0001647543,0.001128454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01621214,"threshold_uncertainty_score":0.03223556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03833291017068889,"score_gpt":0.2608279559890776,"score_spread":0.2224950458183887,"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."}}