{"id":"W2012441343","doi":"10.1016/j.biortech.2006.08.032","title":"Starch industry wastewater as a substrate for antagonist, Trichoderma viride production","year":2006,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Intégré de Santé et de Services Sociaux des Laurentides; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Trichoderma viride; Wastewater; Substrate (aquarium); Pulp and paper industry; Starch; Antagonist; Chemistry; Production (economics); Biotechnology; Sewage treatment; Bioenergy; Food science; Waste management; Biology; Biochemistry; Engineering; Biofuel; Economics; Ecology; 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":[0.0002028612,0.000401017,0.0004106841,0.0002261515,0.0002213041,0.0005731403,0.0003234498,0.0003773705,0.0009291919],"category_scores_gemma":[0.0003074741,0.0001926997,0.000328009,0.0002811637,0.0001088572,0.0002796964,0.0003293313,0.0004517817,0.0004019902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002512975,"about_ca_system_score_gemma":0.0003691421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001427465,"about_ca_topic_score_gemma":0.002587446,"domain_scores_codex":[0.9997328,0.00006957646,0.00002775847,0.00004017272,0.00007798127,0.0000517676],"domain_scores_gemma":[0.9998922,0.00002868905,0.00001436794,0.00001135312,0.00002784619,0.00002536169],"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":[0.00005468941,0.00001147539,0.00007540111,0.0000147669,0.000001985673,0.0000214848,0.000007023133,0.00002633222,0.9991273,0.00001930819,0.00001649001,0.0006238075],"study_design_scores_gemma":[0.000006673134,0.0001191056,0.000460675,0.000003060199,0.000008501712,0.00006229142,0.00002466813,0.0004907313,0.99839,0.00001278487,0.0004186218,0.000003063674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994673,0.0003944398,0.002564735,0.00009151102,0.00002950905,0.00002291363,0.000176338,0.00004724886,0.002000325],"genre_scores_gemma":[0.9930803,0.000310354,0.003229435,0.00002078261,0.000004506907,0.00001281771,0.0002976342,0.00002470228,0.003019545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001427465,"threshold_uncertainty_score":0.003108501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000538202608413,"score_gpt":0.218656250359469,"score_spread":0.2086508683333849,"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."}}