{"id":"W2074413632","doi":"10.1016/j.watres.2005.04.072","title":"Sludge based Bacillus thuringiensis biopesticides: Viscosity impacts","year":2005,"lang":"en","type":"article","venue":"Water Research","topic":"Insect Resistance and Genetics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"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":"Biopesticide; Fermentation; Bacillus thuringiensis; Raw material; Industrial fermentation; Chemistry; Food science; Chemical oxygen demand; Biochemical oxygen demand; Pulp and paper industry; Biotechnology; Environmental science; Environmental engineering; Agronomy; Sewage treatment; Biology; Pesticide; Bacteria; Organic chemistry","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":[0.0002060557,0.0004098051,0.000202849,0.0002667842,0.0001519571,0.0005111585,0.0001692727,0.0003215926,0.001455328],"category_scores_gemma":[0.00042416,0.0001089975,0.0001928809,0.0002651542,0.0001387045,0.0003729625,0.0002405972,0.0004802542,0.0002177935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002510838,"about_ca_system_score_gemma":0.0002170368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008709427,"about_ca_topic_score_gemma":0.00159815,"domain_scores_codex":[0.9997994,0.00004445696,0.00001617558,0.00001717536,0.00008956758,0.00003325224],"domain_scores_gemma":[0.9996639,0.00007664205,0.0001081251,0.00001326189,0.00007444977,0.00006355686],"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":[0.0008420997,0.0001357144,0.0008058341,0.00008454762,0.00001313673,0.00004614823,0.00002164263,0.0004663314,0.9886242,0.00009657631,0.00006630545,0.008797538],"study_design_scores_gemma":[0.00002851743,0.002114862,0.002335146,0.00001469406,0.00003179184,0.00006327062,0.00004600354,0.000678499,0.9939753,0.00007159887,0.0006362002,0.000004120167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965736,0.001241192,0.001004385,0.0001100926,0.00002229516,0.00001247251,0.0001021529,0.00002261842,0.0009112164],"genre_scores_gemma":[0.996071,0.0009878891,0.001173004,0.00003944188,0.000009104523,0.000006487786,0.0001270603,0.000009537402,0.001576359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001455328,"threshold_uncertainty_score":0.004868567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0380016676077644,"score_gpt":0.3349284235994936,"score_spread":0.2969267559917292,"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."}}