{"id":"W2162042027","doi":"10.1029/2008jd009803","title":"The North American Mercury Model Intercomparison Study (NAMMIS): Study description and model‐to‐model comparisons","year":2008,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Air Canada","funders":"National Oceanic and Atmospheric Administration","keywords":"Mercury (programming language); CMAQ; Environmental science; Atmospheric sciences; Meteorology; Climatology; Air quality index; Geology; Geography; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004625846,0.0008146647,0.000637245,0.001626929,0.0007034678,0.001016933,0.001796278,0.0008156915,0.002770784],"category_scores_gemma":[0.006742138,0.0003865901,0.0009500808,0.002758203,0.0002412066,0.0009130265,0.001019764,0.0006034634,0.000386671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753532,"about_ca_system_score_gemma":0.002061666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03723044,"about_ca_topic_score_gemma":0.0221872,"domain_scores_codex":[0.9979889,0.001150511,0.000205089,0.0002604071,0.0002728028,0.0001222219],"domain_scores_gemma":[0.997849,0.0008197441,0.0003877121,0.0004136986,0.0004459208,0.00008398852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004330642,0.002611901,0.693076,0.001490715,0.001931006,0.000968096,0.000718282,0.1598429,0.008208323,0.006825539,0.0245703,0.09542638],"study_design_scores_gemma":[0.002008948,0.002813481,0.78986,0.0003306971,0.00106511,0.000478925,0.00161762,0.09397434,0.01229045,0.002639367,0.09268626,0.0002347974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8913522,0.002686192,0.01536185,0.0006160508,0.0001294405,0.004038528,0.06759265,0.0009186407,0.01730458],"genre_scores_gemma":[0.9030663,0.00147333,0.02593263,0.0005104108,0.0001124439,0.0132294,0.05205301,0.00043725,0.003185218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03723044,"threshold_uncertainty_score":0.07402748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068643188327968,"score_gpt":0.3700488527805021,"score_spread":0.2631845339477053,"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."}}