{"id":"W2942647569","doi":"10.1002/bbb.2015","title":"Development of cost models of algae production in a cold climate using different production systems","year":2019,"lang":"en","type":"article","venue":"Biofuels Bioproducts and Biorefining","topic":"Algal biology and biofuel production","field":"Energy","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Alberta; Cenovus Energy","keywords":"Algae; Biomass (ecology); Environmental science; Biofuel; Tonne; Bioenergy; Photobioreactor; Biology; Botany; Biotechnology; Ecology; Waste management; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008917233,0.000310744,0.0005740765,0.0003527924,0.0001189059,0.00001915348,0.0001290609,0.0002400886,0.00001014325],"category_scores_gemma":[0.00006739973,0.0002417611,0.00004867645,0.0005308389,0.0001861212,0.0002958302,0.0001229877,0.0001831998,0.000006124516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009837429,"about_ca_system_score_gemma":0.00007494224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002767622,"about_ca_topic_score_gemma":0.00006746786,"domain_scores_codex":[0.9974181,0.0001012755,0.0009187614,0.0008829844,0.0002547979,0.0004240709],"domain_scores_gemma":[0.9987283,0.00001417141,0.000555671,0.0004250018,0.0002218473,0.00005503102],"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":[0.000234652,0.0002143088,0.01988608,0.000846898,0.00005567415,6.997249e-7,0.000772473,0.001041078,0.963613,0.002361222,0.000004190238,0.01096972],"study_design_scores_gemma":[0.0005878737,0.0001733908,0.009660804,0.0006664402,0.00004539383,0.00002981772,0.0008715244,0.001494987,0.9848262,0.000178537,0.001006107,0.0004588971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954455,0.001590335,0.00001105469,0.0001082961,0.001786164,0.0008123642,0.00001166889,0.00006646063,0.0001681726],"genre_scores_gemma":[0.9965017,0.0003013196,0.002704841,0.000007055544,0.0002473049,0.00002515512,0.00004256087,0.00002660976,0.0001434255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02121322,"threshold_uncertainty_score":0.9858733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04335269580951345,"score_gpt":0.2479529997715973,"score_spread":0.2046003039620838,"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."}}