{"id":"W2765654819","doi":"10.1016/j.scitotenv.2017.10.289","title":"Molecular characterization of macrophyte-derived dissolved organic matters and their implications for lakes","year":2017,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China; U.S. Department of Agriculture","keywords":"Macrophyte; Environmental science; Characterization (materials science); Environmental chemistry; Ecology; Chemistry; Biology; Materials science; Nanotechnology","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":[0.00009404782,0.0001229433,0.00007790832,0.0002547933,0.0002256241,0.0002699055,0.00007768346,0.0001894851,0.0003777209],"category_scores_gemma":[0.0002592821,0.00008646567,0.00009805395,0.0002650117,0.0001797904,0.0002412459,0.0001680947,0.0001779688,0.00007980783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002035411,"about_ca_system_score_gemma":0.0001882447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002987031,"about_ca_topic_score_gemma":0.005204034,"domain_scores_codex":[0.9999588,0.000006321626,0.000002899517,0.00001464976,0.000007350088,0.00001003899],"domain_scores_gemma":[0.999892,0.00002593221,0.00003628047,0.000006535708,0.00002031279,0.00001897513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001241172,0.00001513939,0.03097164,0.00004451115,0.00001932087,0.00004078917,0.0001697985,0.0001572194,0.9646491,0.0001828284,0.0000466166,0.003578892],"study_design_scores_gemma":[0.00001056029,0.0001902388,0.7124348,0.00001508048,0.00005041753,0.0002303327,0.0006190655,0.002788719,0.2803359,0.0002662028,0.003043594,0.00001513021],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988457,0.0002018984,0.0004306258,0.00002755165,0.000001933991,0.00000254261,0.0002754323,0.000003073608,0.0002112901],"genre_scores_gemma":[0.997443,0.0002247905,0.001260225,0.00002940099,0.000003864711,0.000007684589,0.0004760004,0.000003536123,0.0005515191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002987031,"threshold_uncertainty_score":0.005939305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007355360921532945,"score_gpt":0.1797494336419243,"score_spread":0.1723940727203914,"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."}}