{"id":"W1651385589","doi":"10.4491/eer.2005.10.6.306","title":"IDENTIFICATION OF POSSIBLE MERCURY SOURCES AND ESTIMATION OF MERCURY WET DEPOSITION FLUX IN LAKE ONTARIO FROM LAKE ONTARIO ATMOSPHERIC DEPOSITION STUDY (LOADS)","year":2005,"lang":"en","type":"article","venue":"Environmental Engineering Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Deposition (geology); Environmental science; MERCURE; Flux (metallurgy); Hydrology (agriculture); Precipitation; Environmental chemistry; Meteorology; Geology; Chemistry; Geography; Geomorphology; Sediment; Analytical Chemistry (journal)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006210381,0.0001759824,0.0002404564,0.0000619812,0.000119829,0.00003319861,0.0001478398,0.00007982309,0.001446072],"category_scores_gemma":[0.00002865227,0.0001869978,0.0000405914,0.0002336797,0.000174183,0.0005058129,0.000182763,0.0002935779,0.00006277064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006294206,"about_ca_system_score_gemma":0.00002120429,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0275006,"about_ca_topic_score_gemma":0.4733537,"domain_scores_codex":[0.9980079,0.00009300582,0.0005308309,0.0003475262,0.0007343555,0.0002863963],"domain_scores_gemma":[0.9994258,0.0001116206,0.0001225875,0.0002406017,0.000006349033,0.00009307099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005320347,0.0005601672,0.696353,0.00002188829,0.00004571079,0.000004188663,0.01333645,0.1135508,0.1693535,0.000003335422,0.00004437392,0.006673457],"study_design_scores_gemma":[0.0005393342,0.0001694953,0.947642,0.0000441817,0.00002594285,0.000003720131,0.0006974345,0.01477896,0.03575814,0.00001876468,0.000163796,0.0001582637],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984754,0.0001215335,0.0005863549,0.00003362302,0.00004154737,0.0005227484,0.00003485661,0.00001672003,0.0001671767],"genre_scores_gemma":[0.9974457,0.00003606834,0.00175588,0.000004970165,0.00001823666,0.00004235916,0.0001016179,0.0000184984,0.000576638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4458531,"threshold_uncertainty_score":0.9994667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01383303387769123,"score_gpt":0.255975228981826,"score_spread":0.2421421951041348,"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."}}