{"id":"W2765969197","doi":"10.3390/rs9101063","title":"Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Pacific Salmon Foundation; Marine Environmental Observation Prediction and Response Network; BCFRST Foundation","keywords":"Environmental science; Moderate-resolution imaging spectroradiometer; Atmospheric correction; Remote sensing; Satellite; Reflectivity; Shortwave; Spectroradiometer; Ocean color; Meteorology; Geography; Radiative transfer","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006201745,0.0009346923,0.000594455,0.001430753,0.0007012927,0.001396809,0.000737072,0.0004991519,0.0005269442],"category_scores_gemma":[0.006106938,0.0005008233,0.0007345364,0.002421812,0.0003571029,0.001767884,0.0006425355,0.0003730207,0.0002729284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455425,"about_ca_system_score_gemma":0.002372159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1019089,"about_ca_topic_score_gemma":0.1396082,"domain_scores_codex":[0.998807,0.0001920942,0.0001498526,0.0003492584,0.0004307097,0.00007116359],"domain_scores_gemma":[0.9955024,0.0006148563,0.0006340035,0.0003887318,0.002637495,0.0002225764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001172585,0.0008984536,0.8137956,0.000336256,0.000975478,0.0004599007,0.0009008736,0.03892208,0.01959226,0.0003222997,0.00403427,0.1185901],"study_design_scores_gemma":[0.00009223077,0.0002455367,0.9115837,0.00005835058,0.0002770587,0.00009386788,0.0006054676,0.07404169,0.00792193,0.0001091857,0.004895974,0.00007502716],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927926,0.000255743,0.001765094,0.00007322898,0.00002519213,0.0000911745,0.003449266,0.0002047086,0.001342905],"genre_scores_gemma":[0.9636479,0.0003655347,0.01606398,0.00008325792,0.00001702939,0.0001603511,0.0185109,0.0001040414,0.001047063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1019089,"threshold_uncertainty_score":0.2026315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0390989082355787,"score_gpt":0.2515949690468699,"score_spread":0.2124960608112912,"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."}}