{"id":"W4403901363","doi":"10.5194/amt-17-6301-2024","title":"An improved geolocation methodology for spaceborne radar and lidar systems","year":2024,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"European Space Agency; Jet Propulsion Laboratory; National Aeronautics and Space Administration","keywords":"Geolocation; Remote sensing; Lidar; Environmental science; Radar; Computer science; Meteorology; Geology; Geography; Telecommunications","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":[0.00209953,0.0002486531,0.0002703364,7.884586e-7,0.0001534027,0.0001240218,0.0002148792,0.0001595038,0.0001640519],"category_scores_gemma":[0.00007178776,0.0002097866,0.00006266274,0.0002258923,0.0001300283,0.0002687376,0.00007323937,0.0001225353,0.00001691491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002900945,"about_ca_system_score_gemma":0.00003550115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001179377,"about_ca_topic_score_gemma":0.00006931001,"domain_scores_codex":[0.998193,0.0001753145,0.000314062,0.0006124332,0.0003524168,0.0003527607],"domain_scores_gemma":[0.9992979,0.00007222447,0.00008543909,0.0003681154,0.00004256298,0.0001337825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001162973,0.0001841266,0.005418036,0.0003484455,0.0001378312,0.000009575821,0.0008120905,0.00008573582,0.5254906,0.005076637,0.01050221,0.4518184],"study_design_scores_gemma":[0.001332199,0.006070247,0.01930975,0.0005279044,0.0006537316,0.000146672,0.001984222,0.2441951,0.1071703,0.01647358,0.5991487,0.002987604],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06325842,0.002926491,0.9284557,0.0004434419,0.0003794389,0.001740675,0.000004326508,0.001013725,0.001777752],"genre_scores_gemma":[0.5922992,0.0001438856,0.4064735,0.000127746,0.0001097061,0.0005173847,0.000004845373,0.00004020328,0.0002835768],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5886465,"threshold_uncertainty_score":0.8554848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04012646313275191,"score_gpt":0.2833243526325118,"score_spread":0.2431978894997599,"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."}}