{"id":"W2322558444","doi":"10.1021/ef2018397","title":"Process Optimization Guidance (POG and iPOG) for Mercury Emissions Control","year":2012,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shandong Academy of Sciences; European Commission; Government of Canada","keywords":"Mercury (programming language); Environmental science; Process (computing); Process engineering; Process control; Computer science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0007214778,0.0001701574,0.0002277048,0.00004878589,0.0002523372,0.0001155482,0.0003432774,0.00008218065,0.0003590703],"category_scores_gemma":[0.0005267385,0.0001456757,0.00003082893,0.0001450271,0.0001810075,0.0006678505,0.0000780992,0.00003226111,0.00001506716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000337383,"about_ca_system_score_gemma":0.00008471602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002089557,"about_ca_topic_score_gemma":0.000002558746,"domain_scores_codex":[0.9985693,0.00003812553,0.000299003,0.0003551275,0.0002498986,0.0004885756],"domain_scores_gemma":[0.9990318,0.0001549766,0.0001710085,0.0002793586,0.0001560496,0.000206822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005852323,0.00006806415,0.000162565,0.0001126985,0.000005175078,6.194498e-7,0.0003036931,0.005594957,0.9876783,0.004844772,0.0006350028,0.0005355622],"study_design_scores_gemma":[0.0005823635,0.00005004396,0.0001216897,0.00005631955,0.00003507903,0.00001930051,0.00006089776,0.003287116,0.9872686,0.00216191,0.006062565,0.0002940919],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4595108,0.002530572,0.5320623,0.0006840883,0.001977988,0.0004301918,0.0001297273,0.0002516351,0.002422731],"genre_scores_gemma":[0.983065,0.00003115131,0.01529951,0.0004344668,0.00030601,0.0002332007,0.00001173046,0.00002332024,0.0005956169],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5235542,"threshold_uncertainty_score":0.5940483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160761301257976,"score_gpt":0.2682959212237451,"score_spread":0.2566883082111653,"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."}}