{"id":"W6999394303","doi":"","title":"Contributions to Tsunami Detection by High Frequency Radar","year":2018,"lang":"en","type":"article","venue":"Journal of Media Literacy Education","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radar; Continuous-wave radar; Radar systems; SIGNAL (programming language); Raw data; Radar horizon; Radar imaging; Focus (optics)","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":[0.002028734,0.0008499585,0.0004520249,0.001454318,0.0004978279,0.003043426,0.0009252226,0.001210277,0.00365603],"category_scores_gemma":[0.006089152,0.0004745936,0.000664848,0.001795964,0.0007747939,0.001707362,0.001034652,0.001641725,0.002095191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005658126,"about_ca_system_score_gemma":0.0008281213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008209625,"about_ca_topic_score_gemma":0.000369928,"domain_scores_codex":[0.9985558,0.0002668448,0.00009980215,0.0003808806,0.0006176452,0.00007895505],"domain_scores_gemma":[0.9951945,0.001565883,0.0002232733,0.0005487927,0.002277489,0.0001901131],"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":[0.0003068649,0.000309313,0.005285291,0.00191492,0.0002095231,0.0003420402,0.0008462653,0.03012137,0.02655299,0.07785825,0.02998111,0.8262721],"study_design_scores_gemma":[0.0000822914,0.0009503872,0.007480281,0.0009005098,0.0003016891,0.001873659,0.0006460386,0.1063658,0.04908092,0.05044215,0.7815388,0.0003375856],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04892228,0.1027174,0.7391365,0.0066676,0.02210416,0.0002684031,0.0005098114,0.0009497412,0.07872423],"genre_scores_gemma":[0.3195093,0.1599975,0.3614241,0.003513487,0.05512342,0.0002317896,0.001349693,0.0008781699,0.09797266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00365603,"threshold_uncertainty_score":0.01223063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002999667327823568,"score_gpt":0.2523803687210558,"score_spread":0.2493807013932323,"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."}}