{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001066953,0.0005781904,0.0006641995,0.0001503895,0.001155186,0.00109781,0.0008450798,0.0002465233,0.0001708434],"category_scores_gemma":[0.00005827927,0.0002668824,0.0002094152,0.002896675,0.00200618,0.003107839,0.0003662969,0.001176702,0.000002810529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001397651,"about_ca_system_score_gemma":0.0008354126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002048454,"about_ca_topic_score_gemma":0.0008573241,"domain_scores_codex":[0.9943629,0.0004630095,0.0008669327,0.001685017,0.0007373351,0.001884806],"domain_scores_gemma":[0.998571,0.0002103355,0.0004308513,0.0004262161,0.00007428013,0.0002872765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006070521,0.004201646,0.01802579,0.0005916575,0.0003829027,0.00004589373,0.00168293,0.0004400512,0.8137106,0.05832887,0.001821242,0.09469787],"study_design_scores_gemma":[0.01150868,0.003451537,0.3105436,0.0008207849,0.0004130978,0.0006683265,0.002023665,0.007042309,0.5114083,0.1110001,0.03814818,0.002971393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785161,0.01159085,0.00002852464,0.00725781,0.0003240777,0.00103386,0.0009671341,0.0002062289,0.00007542345],"genre_scores_gemma":[0.9922132,0.0007938936,0.0003245059,0.0001546628,0.0004653149,0.000008050239,0.003442109,0.00001905014,0.002579187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3023024,"threshold_uncertainty_score":0.9999784,"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."}}