{"id":"W2939713472","doi":"10.3389/fmars.2019.00164","title":"The Global High Frequency Radar Network","year":2019,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Networks Canada Society; Dillon Consulting","funders":"National Oceanic and Atmospheric Administration","keywords":"Hfr cell; Radar; Meteorology; Radar systems; Globe; Geography; Telecommunications; Remote sensing; Environmental science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007810988,0.0001130045,0.000132044,0.00001654073,0.0003822258,0.0001504053,0.0009846543,0.00003212985,0.0003622665],"category_scores_gemma":[0.00006494179,0.00007229442,0.00002940111,0.002258034,0.0006749281,0.0004203401,0.00007713876,0.0001272867,0.0000800347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001637091,"about_ca_system_score_gemma":0.0002122144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008722935,"about_ca_topic_score_gemma":0.000419047,"domain_scores_codex":[0.9984255,0.0000293358,0.0001742712,0.0003380319,0.0004354194,0.0005974799],"domain_scores_gemma":[0.9994649,0.00004719188,0.00006520149,0.0002805739,0.000037515,0.0001046202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009567603,0.00000295082,0.9198003,0.000003253868,0.000002261499,0.000003086571,0.000008154769,0.0007152627,5.110402e-7,0.001112091,0.0009822157,0.07736036],"study_design_scores_gemma":[0.0001247306,0.00004080482,0.9158481,0.000007362612,0.000002053615,0.000003480139,0.0001189753,0.001777962,0.000003015361,0.07814898,0.003809951,0.0001146135],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9226601,0.001033489,0.0007747023,0.0004917331,0.005674456,0.0002199503,0.000007385183,0.00005163749,0.06908652],"genre_scores_gemma":[0.9156162,0.0002434426,0.08339095,0.0002248735,0.00009909199,5.576928e-7,0.00000514465,0.000001516594,0.0004182234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08261625,"threshold_uncertainty_score":0.3966564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002478159115608183,"score_gpt":0.1725018099894876,"score_spread":0.1700236508738795,"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."}}