{"id":"W2469082350","doi":"10.1021/acs.energyfuels.6b01438","title":"65th Canadian Chemical Engineering Conference","year":2016,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Process Optimization and Integration","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Biochemical engineering; Chemistry; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001884046,0.0000803588,0.00006375642,0.00006545668,0.00001410062,0.00001941252,0.00008324116,0.00005913744,0.0004523239],"category_scores_gemma":[0.00002557332,0.00006259422,0.00001730604,0.00007424148,0.000008388809,0.0001321501,0.000004940601,0.0000341625,0.00004075175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000805587,"about_ca_system_score_gemma":0.00003700606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008514595,"about_ca_topic_score_gemma":0.001724147,"domain_scores_codex":[0.9996105,0.000002274031,0.00008565024,0.00008139316,0.00005364378,0.0001665706],"domain_scores_gemma":[0.9997296,0.00001035068,0.000006509745,0.00008740165,0.00003540537,0.0001307097],"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":[0.00000224142,0.000006477131,0.00006131103,0.00001804183,0.00003062546,0.000005344879,0.0001089434,0.008568458,0.848305,0.08487184,0.005389379,0.05263231],"study_design_scores_gemma":[0.0001687851,0.000006727794,0.00005537934,0.0000449122,0.000003347084,0.000003797899,0.000004875414,0.03265236,0.8505867,0.000256838,0.1159987,0.0002176518],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0932906,0.0003879735,0.8059002,0.0008543534,0.0008353134,0.00006054791,0.000029447,0.00097249,0.09766904],"genre_scores_gemma":[0.9979734,0.00006955516,0.0009834353,0.000090765,0.00007194606,0.00001172529,0.000009181058,0.00001702669,0.0007729837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9046828,"threshold_uncertainty_score":0.495263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006554719374385573,"score_gpt":0.1715764536249063,"score_spread":0.1650217342505207,"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."}}