{"id":"W4312983164","doi":"10.14321/aehm.025.02.01","title":"Application of the Laurentian Great Lakes ‘Ecosystem Approach’ towards remediation and restoration of the mighty River Ganges, India","year":2022,"lang":"en","type":"article","venue":"Aquatic Ecosystem Health & Management","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Industrial Plankton; Fisheries and Oceans Canada","funders":"","keywords":"Environmental remediation; Watershed; Ecosystem; Environmental planning; Eutrophication; Environmental resource management; Environmental restoration; Geography; Environmental protection; Water resource management; Environmental science; Ecology; Contamination","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001728075,0.0001688113,0.0003210108,0.00005749005,0.0004536422,0.00001490053,0.000495539,0.00004497924,0.00006994367],"category_scores_gemma":[0.00001453567,0.0001153789,0.00008173742,0.0005256161,0.00005420807,0.00009139322,0.0004677088,0.0001350133,0.00001018279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005616412,"about_ca_system_score_gemma":0.00004175219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001436953,"about_ca_topic_score_gemma":0.009150963,"domain_scores_codex":[0.9971064,0.0006780123,0.0008129641,0.0003166526,0.0008523198,0.0002336886],"domain_scores_gemma":[0.9979033,0.00005197325,0.001210652,0.0007552976,0.00001244875,0.00006626833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001249601,0.001001926,0.7533976,0.0157621,0.0004718869,0.000002580909,0.03365801,0.04629396,0.0002435621,0.05020296,0.01969984,0.07914058],"study_design_scores_gemma":[0.001421755,0.0002527803,0.5204149,0.0003554463,0.0002078608,0.00002272895,0.005072313,0.4127423,0.00006891262,0.001600766,0.05737864,0.0004615889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796885,0.0003935287,0.007982737,0.001519274,0.0007797168,0.005696682,0.0002151204,0.00003725341,0.003687199],"genre_scores_gemma":[0.9986724,0.00003131545,0.0004716836,0.0001380875,0.00002759657,0.0003588758,0.00005555681,0.00001695414,0.000227476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3664484,"threshold_uncertainty_score":0.5106452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00862637231982014,"score_gpt":0.2094154284870643,"score_spread":0.2007890561672442,"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."}}