{"id":"W7027763291","doi":"","title":"Drone-based ground-penetrating radar for glaciological applications","year":2024,"lang":"en","type":"dissertation","venue":"IRIS","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ground-penetrating radar; Radar; Glacier; Climate change; Sea ice; Glaciology; Synthetic aperture radar","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":[0.0003043047,0.0004623082,0.0002463686,0.0004645326,0.0001051305,0.0005038254,0.0004343779,0.0006544745,0.005757872],"category_scores_gemma":[0.0003971743,0.0001847833,0.0002428748,0.000457964,0.0001108354,0.0005397301,0.0004051648,0.0005728121,0.003097813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001569114,"about_ca_system_score_gemma":0.0002191406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004712498,"about_ca_topic_score_gemma":0.0005739631,"domain_scores_codex":[0.9998232,0.00002641114,0.000007158941,0.00003145224,0.00009294088,0.00001887774],"domain_scores_gemma":[0.9997897,0.0000452405,0.00001856334,0.00004716576,0.00008448912,0.00001488765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001970249,0.0001314121,0.001860677,0.0005130991,0.00004497354,0.0004191431,0.0002371175,0.006961966,0.41434,0.005277039,0.02399822,0.5460192],"study_design_scores_gemma":[0.0001810558,0.00106331,0.01079747,0.000370927,0.0001583112,0.002481304,0.000381085,0.2124798,0.2624218,0.005655955,0.5038618,0.000147276],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07494846,0.007500554,0.8646138,0.0007995535,0.0006333729,0.0005488395,0.001886599,0.01134533,0.03772345],"genre_scores_gemma":[0.4217597,0.008774724,0.5309802,0.001099731,0.0002595357,0.000421015,0.003611913,0.0005654375,0.03252777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005757872,"threshold_uncertainty_score":0.01926202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02151352705007569,"score_gpt":0.309205497664948,"score_spread":0.2876919706148723,"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."}}