{"id":"W1873343829","doi":"10.1039/c5ra14470a","title":"Low cost semi-continuous bioprocess and online monitoring of hydrogen production from crude glycerol","year":2015,"lang":"en","type":"article","venue":"RSC Advances","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre de Recherche Industrielle du Québec; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Bioprocess; Glycerol; Production (economics); Process engineering; Hydrogen production; Pulp and paper industry; Hydrogen; Process (computing); Production cost; Chemistry; Biochemical engineering; Environmental science; Computer science; Chemical engineering; Engineering; Economics; Organic chemistry; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004695054,0.0003426523,0.000307216,0.0003248871,0.0002388218,0.000728662,0.0009071965,0.0005002798,0.00081037],"category_scores_gemma":[0.0005680708,0.0002147601,0.0002524911,0.0004009932,0.0003381749,0.0008231582,0.0008212767,0.0007370762,0.0003690847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004293005,"about_ca_system_score_gemma":0.0005471775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001244901,"about_ca_topic_score_gemma":0.002439456,"domain_scores_codex":[0.9995162,0.00005634737,0.00002554944,0.00008353364,0.0002788579,0.00003952083],"domain_scores_gemma":[0.9997194,0.00008773408,0.000043717,0.00004864062,0.00006724803,0.00003322004],"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":[0.0002898726,0.00006841082,0.0007983294,0.0001233508,0.00001338204,0.00007301446,0.00003164954,0.0003691257,0.9814786,0.0003238296,0.0002002311,0.01623023],"study_design_scores_gemma":[0.00002096297,0.0002119321,0.002005863,0.000006211434,0.00002338098,0.00015356,0.00003832965,0.01151143,0.9843593,0.000125568,0.001526824,0.00001653146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.924439,0.001345009,0.07062256,0.000512596,0.00009080122,0.0001247736,0.0007056812,0.0003452137,0.00181435],"genre_scores_gemma":[0.9666695,0.0004546571,0.030528,0.00004035534,0.0000233188,0.00005991588,0.0003550725,0.00002385638,0.00184524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001244901,"threshold_uncertainty_score":0.00311482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044315149900492,"score_gpt":0.2496393192931853,"score_spread":0.2391961677941804,"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."}}