{"id":"W2910485092","doi":"10.1016/j.jclepro.2019.01.111","title":"Thin stillage treatment and co-production of bio-commodities through finely tuned Chlorella vulgaris cultivation","year":2019,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Algal biology and biofuel production","field":"Energy","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chlorella vulgaris; Stillage; Phytoremediation; Pulp and paper industry; Effluent; Biomass (ecology); Food science; Biofuel; Chemistry; Photosynthesis; Bioenergy; Photosynthetic efficiency; Botany; Biotechnology; Biology; Environmental science; Algae; Environmental engineering; Environmental chemistry; Fermentation; Agronomy; Engineering","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":[0.00004691886,0.0003108066,0.0001860038,0.0001670185,0.0001197475,0.0003734501,0.0001445996,0.0002182968,0.00078637],"category_scores_gemma":[0.00006022709,0.0001405222,0.0002869312,0.0001642981,0.0001592271,0.0002001293,0.00031336,0.0003750294,0.0002022627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001926437,"about_ca_system_score_gemma":0.0001664743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000908694,"about_ca_topic_score_gemma":0.002188148,"domain_scores_codex":[0.9999315,0.000002389698,0.000003641124,0.00001786559,0.00002179354,0.00002283226],"domain_scores_gemma":[0.9999617,0.000005468653,0.00001081727,0.000004180098,0.000006499924,0.0000111744],"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":[0.00002438339,0.000005675732,0.00004032517,0.000009812596,0.00000106533,0.00001530734,0.00000407831,0.00004369607,0.9994428,0.00001619857,0.000008939038,0.0003876871],"study_design_scores_gemma":[0.000004560483,0.00004668563,0.0007082784,0.000001435118,0.000005733541,0.00001687056,0.00001148566,0.0004831974,0.9982243,0.00001403425,0.0004801127,0.000003387383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954656,0.0003434139,0.002564599,0.00004161519,0.00003725626,0.00001212921,0.0001257997,0.00007176513,0.001337794],"genre_scores_gemma":[0.9973097,0.000206052,0.0009215388,0.00001616953,0.000003434965,0.000007300839,0.00007923335,0.00001444159,0.001442156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000908694,"threshold_uncertainty_score":0.002630651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357155079717562,"score_gpt":0.2631089750547182,"score_spread":0.2395374242575426,"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."}}