{"id":"W4391838688","doi":"10.1080/10402381.2023.2299868","title":"A lake management framework for global application: monitoring, restoring, and protecting lakes through community engagement","year":2024,"lang":"en","type":"article","venue":"Lake and Reservoir Management","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Regina; Toronto Metropolitan University","funders":"Agencia Estatal de Investigación; Wageningen University and Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministerie van Landbouw, Natuur en Voedselkwaliteit; Grantová Agentura České Republiky; European Social Fund; Biodiversa+; Bundesministerium für Bildung und Forschung; European Regional Development Fund; Global Lake Ecological Observatory Network; Joint Programming Initiative Water challenges for a changing world","keywords":"Environmental resource management; Environmental science; Community engagement; Environmental planning; Water resource management; Hydrology (agriculture); Political science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001304371,0.0002685583,0.0001923721,0.00004792831,0.000912643,0.0003066795,0.0005089084,0.0001221171,0.00002074649],"category_scores_gemma":[0.00004305181,0.0002394779,0.00005488456,0.0003571762,0.0002171884,0.0002732463,0.002088104,0.0004814286,0.00002552662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001610563,"about_ca_system_score_gemma":0.00000227674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355454,"about_ca_topic_score_gemma":0.0004516723,"domain_scores_codex":[0.9981177,0.0001568589,0.0002983393,0.0005956074,0.0003867488,0.0004447555],"domain_scores_gemma":[0.9989568,0.0001355972,0.00006669907,0.000762096,0.000008760422,0.00007004546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001827889,0.0006187178,0.1261164,0.009266667,0.00113961,0.0001909582,0.008943195,0.001222255,0.0001750091,0.4848458,0.006662594,0.360636],"study_design_scores_gemma":[0.0003973629,0.0001819269,0.05024111,0.0006563156,0.0001304975,0.000006183977,0.004608229,0.0002925105,0.0004900447,0.212391,0.7301344,0.0004703595],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556535,0.00158825,0.1033077,0.005199097,0.001259779,0.005562564,0.00005825924,0.001982855,0.02538802],"genre_scores_gemma":[0.8798568,0.0009027412,0.1150616,0.00006312305,0.0001974936,0.00186274,0.0000131485,0.00003656893,0.002005826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7234718,"threshold_uncertainty_score":0.9765624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06739124446236108,"score_gpt":0.3263209977293057,"score_spread":0.2589297532669446,"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."}}