{"id":"W2802625149","doi":"","title":"Collection of Environmental Radar Data Using a Tactical Shipborne Radar","year":2001,"lang":"en","type":"article","venue":"The 81st AMS Annual Meeting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Radar; Remote sensing; Early-warning radar; Meteorology; Geology; Environmental science; Aeronautics; Computer science; Radar imaging; Radar engineering details; Geography; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005229932,0.000325127,0.0003674836,0.0009019086,0.0005099003,0.0005557887,0.0003723156,0.0003563037,0.002005861],"category_scores_gemma":[0.001018002,0.0002212326,0.0002267753,0.0008735853,0.000149452,0.0006348272,0.0006028472,0.0004266624,0.001233376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002079332,"about_ca_system_score_gemma":0.0006408393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005018587,"about_ca_topic_score_gemma":0.01149698,"domain_scores_codex":[0.9996709,0.00005315391,0.00001730404,0.00005380069,0.0001563421,0.00004858119],"domain_scores_gemma":[0.9991928,0.00007447744,0.00004576208,0.0002805738,0.0003390818,0.00006727597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007237493,0.0009218265,0.09283966,0.0002179958,0.0002763667,0.0006344094,0.0006790157,0.1132773,0.230402,0.002781826,0.04667924,0.5105666],"study_design_scores_gemma":[0.0003919442,0.0007538588,0.183681,0.00004897352,0.0002969713,0.000547145,0.0005734013,0.6286641,0.1082888,0.00294877,0.07361547,0.0001895674],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6308747,0.0002748799,0.3069557,0.0004819933,0.0004166668,0.000832388,0.01592043,0.009716297,0.034527],"genre_scores_gemma":[0.7769511,0.0002627923,0.1930943,0.000243447,0.0001447244,0.0003033543,0.02357211,0.0002921556,0.005135986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005018587,"threshold_uncertainty_score":0.009978771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05440793203433088,"score_gpt":0.2582128748336986,"score_spread":0.2038049427993677,"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."}}