{"id":"W4299335026","doi":"10.5281/zenodo.6802819","title":"Mayfly Metric of the Lake Erie Quality Index: Design of an Efficient Censusing Program, Data Collection, and Development of the Metric","year":2004,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Water Quality and Resources Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ohio Sea Grant College, Ohio State University; U.S. Geological Survey; University of Windsor; Oregon Health and Science University","keywords":"Metric (unit); Metric system; Mayfly; Index (typography); Tonne; Quality (philosophy); Geography; Computer science; Ecology; Engineering; Operations management; Archaeology; Biology; World Wide Web; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003546179,0.0001657052,0.0003031781,0.0001922682,0.001543894,0.00009244922,0.001573885,0.00009949503,0.0007967515],"category_scores_gemma":[0.001502277,0.0001071706,0.00004721035,0.002186111,0.0008369322,0.00007305585,0.005169311,0.0002540519,0.00002137439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003322439,"about_ca_system_score_gemma":0.00004692064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002611359,"about_ca_topic_score_gemma":0.00003906668,"domain_scores_codex":[0.9964108,0.0008897444,0.0006552504,0.0004379276,0.001373212,0.0002331075],"domain_scores_gemma":[0.9979918,0.00005229699,0.0006980859,0.0008718871,0.0003187835,0.00006717321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006937612,0.007293427,0.00564667,0.00618526,0.001826693,0.00001126111,0.05071613,0.06457794,0.004412608,0.0001811822,0.1139604,0.7444947],"study_design_scores_gemma":[0.0004685314,0.0001954232,0.1022911,0.0001737123,0.00008113493,0.00003987424,0.0007365892,0.0003918377,0.001914375,0.00002631235,0.8934346,0.0002464432],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7985101,0.002946806,0.03242989,0.001120573,0.001488655,0.01563646,0.005485573,0.0008920226,0.1414899],"genre_scores_gemma":[0.9934533,0.0002483853,0.004022957,0.00001948535,0.00004566891,2.543e-7,0.0006162209,0.0005702321,0.001023542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7794743,"threshold_uncertainty_score":0.999756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2114051754922096,"score_gpt":0.3124981501537111,"score_spread":0.1010929746615014,"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."}}