{"id":"W4220998548","doi":"10.1016/j.algal.2022.102679","title":"Techno-economic analysis of microalgae production for aquafeed in Norway","year":2022,"lang":"en","type":"article","venue":"Algal Research","topic":"Algal biology and biofuel production","field":"Energy","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Networks of Centres of Excellence of Canada; Universidad de Cádiz","keywords":"Biomass (ecology); Productivity; Environmental science; Capital cost; Biofuel; Phaeodactylum tricornutum; Pulp and paper industry; Newsprint; Production (economics); Aquaculture; Sustainability; Greenhouse; Agricultural science; Biotechnology; Environmental engineering; Biology; Ecology; Fishery; Engineering; Agronomy; Fish <Actinopterygii>; Algae; Economics","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":[0.001097199,0.0003544975,0.0003989905,0.0008991234,0.0005434412,0.001085303,0.0003753948,0.0003155326,0.001129198],"category_scores_gemma":[0.000747334,0.0001651605,0.0008974638,0.0008298992,0.0003683982,0.0006299999,0.0004464962,0.000260496,0.000134016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008252902,"about_ca_system_score_gemma":0.002704009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1064057,"about_ca_topic_score_gemma":0.1172809,"domain_scores_codex":[0.9993328,0.0001140812,0.00005613719,0.0001081831,0.0002526006,0.0001362274],"domain_scores_gemma":[0.9995676,0.000166903,0.00007250346,0.00001994032,0.0001202794,0.00005293415],"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":[0.009602232,0.001095799,0.1486091,0.001495524,0.0003003761,0.002333541,0.0004391319,0.3712741,0.3333756,0.004996867,0.000928185,0.1255496],"study_design_scores_gemma":[0.000169221,0.006374076,0.6048113,0.0002362198,0.0004801196,0.0006346348,0.003407941,0.1295631,0.2340801,0.002376789,0.0177011,0.0001653442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942741,0.0006159558,0.00116364,0.00003872015,0.00001558633,0.00004910928,0.0005505045,0.00001005428,0.003282201],"genre_scores_gemma":[0.9964821,0.0004855835,0.001178202,0.00001056216,0.000003231793,0.00003143648,0.0004649191,0.000008149131,0.001335821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1064057,"threshold_uncertainty_score":0.2115728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05521532168669507,"score_gpt":0.3560596895557124,"score_spread":0.3008443678690174,"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."}}