{"id":"W4323821264","doi":"10.1002/9783527827992.ch48","title":"The <scp>NORAM</scp> Process for the Production of Nitrobenzene (Case Study)","year":2023,"lang":"en","type":"other","venue":"","topic":"Thermal and Kinetic Analysis","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"NORAM (Canada)","funders":"","keywords":"Sulfuric acid; Nitration; Chemistry; Nitric acid; Nitrobenzene; Organic chemistry; Catalysis","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":[0.0007479906,0.0003961025,0.0002503858,0.0004730638,0.001696842,0.001344623,0.0009494848,0.00147896,0.007426815],"category_scores_gemma":[0.0007620386,0.0001585763,0.0005399452,0.0009023619,0.0006212391,0.001228793,0.000853079,0.0007841771,0.00201993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001494134,"about_ca_system_score_gemma":0.001284627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061654,"about_ca_topic_score_gemma":0.01728353,"domain_scores_codex":[0.9990395,0.0001731831,0.00003494378,0.0001298968,0.0004588906,0.0001636977],"domain_scores_gemma":[0.9997062,0.00007901865,0.000033106,0.0000392076,0.0000931904,0.00004916389],"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":[0.00196865,0.002753847,0.02680215,0.00444587,0.0001191165,0.08379826,0.00641082,0.04563567,0.2361366,0.1000592,0.09175833,0.4001114],"study_design_scores_gemma":[0.00009444075,0.001557692,0.0122366,0.0004168448,0.00006365742,0.01960917,0.004720723,0.0181736,0.185536,0.006001746,0.7514833,0.0001061799],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6087748,0.00571555,0.03353929,0.003650505,0.0005200443,0.0008335812,0.002026411,0.0006076827,0.3443322],"genre_scores_gemma":[0.8814791,0.003559378,0.04207236,0.0004898687,0.00009123302,0.0001881358,0.001196164,0.0001855803,0.07073817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01061654,"threshold_uncertainty_score":0.02484524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02557131197138627,"score_gpt":0.2867547890539018,"score_spread":0.2611834770825155,"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."}}