{"id":"W2317547572","doi":"10.7763/jocet.2014.v2.135","title":"Progress of Global Atmospheric Mercury Field Observations","year":2013,"lang":"en","type":"article","venue":"Journal of Clean Energy Technologies","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Mercury (programming language); Environmental science; Field (mathematics); Atmospheric sciences; Geology; Computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002829185,0.001198528,0.0007283679,0.008071729,0.000526652,0.001317981,0.000920428,0.0007956662,0.003248867],"category_scores_gemma":[0.002380165,0.0003739107,0.0009164172,0.008140205,0.0002988652,0.003690263,0.0015137,0.0009870722,0.00157921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488895,"about_ca_system_score_gemma":0.004300308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02502771,"about_ca_topic_score_gemma":0.01788227,"domain_scores_codex":[0.9989273,0.0001273324,0.0001061241,0.0002864275,0.0004683188,0.00008445651],"domain_scores_gemma":[0.9965834,0.0003655562,0.0002574737,0.0002494828,0.002401486,0.0001427259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001417437,0.00005057869,0.04616791,0.005324814,0.0002099686,0.0002187469,0.0002601799,0.003700434,0.004453832,0.004462022,0.1406403,0.7943696],"study_design_scores_gemma":[0.00002164803,0.00008927401,0.04000413,0.001013294,0.0002566223,0.0002074745,0.0002780343,0.002659708,0.005350537,0.001907464,0.9481427,0.00006911666],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.07344663,0.5679819,0.07192767,0.02369149,0.01706494,0.0007266125,0.1024024,0.007958788,0.1347995],"genre_scores_gemma":[0.2697428,0.4657066,0.07765479,0.008186402,0.008603655,0.0004351259,0.128505,0.002690856,0.03847477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02502771,"threshold_uncertainty_score":0.0497641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261112619268195,"score_gpt":0.223072560195844,"score_spread":0.210461434003162,"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."}}