{"id":"W4301387776","doi":"","title":"DETECTION OF MESOSCALE OCEANIC FEATURES USING RADARSAT-1, AVHRR AND SEAWIFS IMAGES AND THE POSSIBLE LINK WITH JACK MACKEREL (TRACHURUS MURPHYI) DISTRIBUTION IN CENTRAL CHILE","year":2004,"lang":"en","type":"article","venue":"Scientific Electronic Library Online (Scientific Electronic Library Online)","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut du Savoir Montfort","funders":"","keywords":"SeaWiFS; Geography; Mesoscale meteorology; Oceanography; Fishery; Environmental science; Geology; Biology; Ecology; Phytoplankton","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001421189,0.0001430125,0.00009082457,0.0006348554,0.0001097934,0.0003360041,0.0001134952,0.0001067474,0.0005779885],"category_scores_gemma":[0.0003245231,0.0001374246,0.0000997637,0.0003239914,0.0001563382,0.0002240153,0.0002278707,0.00008767096,0.0001070513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003092758,"about_ca_system_score_gemma":0.0002403308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01986939,"about_ca_topic_score_gemma":0.0369124,"domain_scores_codex":[0.9999411,0.000007805896,0.000004929332,0.00001862193,0.00001279482,0.00001486382],"domain_scores_gemma":[0.9998448,0.00002570646,0.00005568381,0.0000121619,0.00002892171,0.00003269508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000249901,0.00006863435,0.8858886,0.00009347063,0.00005586525,0.000501911,0.0006298038,0.001843887,0.08450586,0.0001442019,0.0002664176,0.02575126],"study_design_scores_gemma":[0.000009098366,0.00002424024,0.9962681,0.000005944651,0.000010316,0.00006552778,0.0003383764,0.001341618,0.001670004,0.00002224503,0.0002399791,0.00000456027],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993297,0.00002637591,0.00007633535,0.00001045894,3.936184e-7,0.000004161447,0.0001301966,0.000005590928,0.0004168784],"genre_scores_gemma":[0.9990078,0.00002953345,0.0003501241,0.000005295243,7.738778e-7,0.000006829185,0.0002222222,0.000001219297,0.0003763354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01986939,"threshold_uncertainty_score":0.03950745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00833314246288341,"score_gpt":0.2034460969478887,"score_spread":0.1951129544850053,"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."}}