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Near shore sediment diatoms of the great lakes and their use as biological indicators","year":2003,"lang":"en","type":"article","venue":"Journal of Phycology","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shore; Sediment; Water quality; Environmental science; Ecosystem; Sampling (signal processing); Lake ecosystem; Hydrology (agriculture); Nutrient; Oceanography; Ecology; Physical geography; Biology; Geography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003822172,0.0001386271,0.000133764,0.00114345,0.0003479296,0.0005849509,0.0001135487,0.00009686033,0.00031959],"category_scores_gemma":[0.0005367098,0.0001468544,0.00006081687,0.001419256,0.0002550767,0.0002378266,0.0004600767,0.000148899,0.0001026161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004278115,"about_ca_system_score_gemma":0.0003310523,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01965339,"about_ca_topic_score_gemma":0.09336023,"domain_scores_codex":[0.9997842,0.00006658295,0.0000140826,0.0000342362,0.00008436973,0.00001654137],"domain_scores_gemma":[0.999778,0.00004293459,0.00007374184,0.00001227233,0.00005764475,0.00003539181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000812926,0.00001507882,0.9311689,0.00006187311,0.00005326486,0.00007138564,0.00075191,0.0003507946,0.01771297,0.0003538383,0.0005986682,0.04878004],"study_design_scores_gemma":[0.000002054819,0.00003803823,0.9958403,0.000007596901,0.000009009292,0.00005587947,0.0001704469,0.0002961888,0.001113589,0.0001022904,0.00236102,0.000003635555],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951705,0.0009831561,0.0003644579,0.00005715802,0.00000336011,0.000008495806,0.0004399027,0.000008102303,0.002964851],"genre_scores_gemma":[0.9952959,0.0009660616,0.001809437,0.00002616051,0.000007190493,0.00001459249,0.0008227879,0.00000360944,0.001054182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9803466,"threshold_uncertainty_score":0.039078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043318641950362,"score_gpt":0.2082688808182705,"score_spread":0.1978356943987669,"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."}}