{"id":"W2291997619","doi":"10.5988/jime.50.101","title":"Alfa Laval Green Technology - SOx Reduction Technology for ECA and Fuel Recovery Solution","year":2015,"lang":"en","type":"article","venue":"Marine Engineering","topic":"Iron and Steelmaking Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Reduction (mathematics); Automotive engineering; Environmental science; Waste management; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113461,0.0001713032,0.0001835922,0.0004688326,0.00003432712,0.00002214066,0.0001060304,0.0002202494,0.000003898865],"category_scores_gemma":[0.00008936218,0.0001937835,0.000025503,0.0003434146,0.00002953562,0.0001411049,0.00009409507,0.0001886852,0.000005923184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008723879,"about_ca_system_score_gemma":0.00001619692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002092909,"about_ca_topic_score_gemma":0.00001723124,"domain_scores_codex":[0.9992645,0.000002351263,0.0001723793,0.0001908202,0.00007111098,0.0002988856],"domain_scores_gemma":[0.9996905,0.00001295784,0.00002212253,0.0001631985,0.00005624336,0.00005502389],"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":[0.0001386354,0.00008322144,0.002526344,0.002669714,0.0003077723,0.00003050485,0.0006285497,0.1894533,0.07122982,0.0373659,0.005518321,0.690048],"study_design_scores_gemma":[0.002227016,0.0005389396,0.0008283125,0.0001428957,0.00009573163,0.0006321457,0.0003648194,0.3613511,0.04164835,0.009253688,0.5816901,0.001226869],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5938171,0.009921896,0.3570305,0.004512049,0.006543772,0.001517178,0.00003511166,0.01208515,0.01453722],"genre_scores_gemma":[0.9807938,0.0002021986,0.01687225,0.000005775649,0.0002475116,0.000109347,0.00001751908,0.00007207744,0.001679485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6888211,"threshold_uncertainty_score":0.7902263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009246304021302998,"score_gpt":0.1963781107367246,"score_spread":0.1871318067154216,"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."}}