{"id":"W2290157384","doi":"10.3389/fmars.2016.00007","title":"Predicting Dissolved Lignin Phenol Concentrations in the Coastal Ocean from Chromophoric Dissolved Organic Matter (CDOM) Absorption Coefficients","year":2016,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut national des sciences de l'Univers; Government of Canada; National Oceanic and Atmospheric Administration; Japan Agency for Marine-Earth Science and Technology; Office of Naval Research; Centre National de la Recherche Scientifique; Ministry of Education, Culture, Sports, Science and Technology; Centre National d’Etudes Spatiales; National Science Foundation; European Space Agency; National Aeronautics and Space Administration; Agence Nationale de la Recherche","keywords":"Colored dissolved organic matter; Dissolved organic carbon; Lignin; Terrigenous sediment; Environmental chemistry; Spectral slope; Environmental science; Organic matter; Absorption (acoustics); Chemistry; Oceanography; Nutrient; Sediment; Geology; Phytoplankton","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009191612,0.0006597976,0.0003444896,0.0005084671,0.0002288256,0.001119449,0.0004479751,0.0005879006,0.0004906546],"category_scores_gemma":[0.002021392,0.0003631849,0.0006847839,0.0006320082,0.000191459,0.0004996296,0.0005568914,0.0005532868,0.0002562814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007422401,"about_ca_system_score_gemma":0.0007615707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02014099,"about_ca_topic_score_gemma":0.01918259,"domain_scores_codex":[0.9998222,0.00004347909,0.00001290735,0.00007678669,0.00002301225,0.00002167709],"domain_scores_gemma":[0.9992818,0.0004048611,0.0001208653,0.00005278615,0.0000984895,0.00004108269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003870396,0.0003303249,0.7026206,0.0001058406,0.0002349762,0.0001296164,0.0001553839,0.2219596,0.03211532,0.0003687902,0.0002942799,0.04129821],"study_design_scores_gemma":[0.00003031819,0.00009583314,0.2021921,0.00001037958,0.00005246963,0.00002773649,0.0001104187,0.791275,0.005478176,0.0003849617,0.0003164957,0.00002616062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894094,0.00006502654,0.009747222,0.00003833132,0.000003168882,0.00001612964,0.0003106726,0.000071581,0.0003383432],"genre_scores_gemma":[0.9890828,0.00007985017,0.009799117,0.00001365954,0.000002677227,0.00002439211,0.0006658368,0.00001095129,0.0003207019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02014099,"threshold_uncertainty_score":0.04004747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005965663662635624,"score_gpt":0.1872802668758383,"score_spread":0.1813146032132027,"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."}}