{"id":"W2964350699","doi":"10.1002/bit.27128","title":"Increasing productivity of <i>Spirulina platensis</i> in photobioreactors using artificial neural network modeling","year":2019,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"Algal biology and biofuel production","field":"Energy","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Central Food Technological Research Institute, Council of Scientific and Industrial Research; Grand Challenges Canada","keywords":"Spirulina (dietary supplement); Photobioreactor; Productivity; Biomass (ecology); Growth rate; Biology; Food science; Cyanobacteria; Animal science; Pulp and paper industry; Environmental science; Botany; Biotechnology; Chemistry; Mathematics; Ecology; Engineering; Economics; Raw material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003142033,0.0007166076,0.0004122291,0.0002934512,0.000209491,0.0005162553,0.00045708,0.0006198301,0.0004711212],"category_scores_gemma":[0.0002935068,0.0003071018,0.0006551254,0.0002489898,0.0001639069,0.0003708236,0.0002340836,0.0004223392,0.000133243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009275574,"about_ca_system_score_gemma":0.0004208187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01588472,"about_ca_topic_score_gemma":0.01412514,"domain_scores_codex":[0.9999157,0.00001111718,0.000006182734,0.00003342536,0.0000218845,0.00001157045],"domain_scores_gemma":[0.9998813,0.00004322704,0.00003298534,0.000004299895,0.00003092328,0.00000726853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009096945,0.000114367,0.002902671,0.0001168039,0.00004557311,0.00008486729,0.00002837343,0.9250184,0.05657208,0.0001483433,0.0001140622,0.01476343],"study_design_scores_gemma":[0.00000138128,0.0000470168,0.0006111346,0.000002496816,0.000007064627,0.000003263363,0.000003777097,0.9934881,0.005756122,0.00002690081,0.00004887705,0.000003862268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9059085,0.0006069306,0.08913334,0.0001731725,0.00003525719,0.00005189286,0.0001304604,0.0004397742,0.003520797],"genre_scores_gemma":[0.9896089,0.0002180748,0.008848566,0.0000208546,0.000003053321,0.0000384635,0.00006541575,0.000007867559,0.001188815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01588472,"threshold_uncertainty_score":0.03158456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01683915175111169,"score_gpt":0.2097114365512742,"score_spread":0.1928722848001626,"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."}}