{"id":"W2124622454","doi":"10.5194/bgd-9-9487-2012","title":"The 1% and 1 cm perspective in deriving and validating AOP data products","year":2012,"lang":"en","type":"article","venue":"","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Remote sensing; Colored dissolved organic matter; Environmental science; SeaWiFS; Backplane; Seawater; Buoyancy; Data acquisition; Ranging; Data set; Water quality; Computer science; Geology; Physics; Telecommunications; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.03903532,0.002050535,0.001201508,0.002992369,0.000865882,0.005890988,0.003632411,0.003214505,0.001309343],"category_scores_gemma":[0.07731896,0.001287401,0.001011236,0.002683798,0.002971469,0.007725633,0.005412008,0.005622627,0.001071525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0020328,"about_ca_system_score_gemma":0.002636867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004887279,"about_ca_topic_score_gemma":0.002627947,"domain_scores_codex":[0.9709357,0.009891569,0.001703317,0.00333805,0.01356597,0.0005654172],"domain_scores_gemma":[0.9144097,0.04178355,0.009415736,0.01542342,0.01797169,0.0009958942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009587371,0.0007511487,0.08707368,0.00232134,0.0008935002,0.000787776,0.001714847,0.08148123,0.1942912,0.09306636,0.008569462,0.5280908],"study_design_scores_gemma":[0.00009150177,0.001690119,0.08369064,0.001542942,0.0005307142,0.001912705,0.001747622,0.3340388,0.3053641,0.1145305,0.1542775,0.0005828706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1329466,0.005994411,0.8291074,0.007785405,0.001135679,0.0003154359,0.003512061,0.003318518,0.01588448],"genre_scores_gemma":[0.3216496,0.001496575,0.6693076,0.002252102,0.0004573701,0.0002907292,0.002466897,0.0006897894,0.001389423],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03903532,"threshold_uncertainty_score":0.206441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0357429442520234,"score_gpt":0.2380248155630506,"score_spread":0.2022818713110272,"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."}}