{"id":"W1680785731","doi":"10.5296/emsd.v4i2.8182","title":"Efficiency and Environmental Metrics of Algal Fuel","year":2015,"lang":"en","type":"article","venue":"Environmental Management and Sustainable Development","topic":"Algal biology and biofuel production","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Subsidy; Greenhouse gas; Fossil fuel; Renewable energy; Biofuel; Biomass (ecology); Environmental science; Entitlement (fair division); Natural resource economics; Fuel efficiency; Renewable fuels; Economics; Waste management; Ecology; Engineering; Biology; Automotive engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004507387,0.0001922186,0.0001731324,0.0001764404,0.0001552191,0.00001815949,0.00009956086,0.00007882617,0.00008258973],"category_scores_gemma":[0.000008756213,0.0001746359,0.00002156733,0.0001166232,0.0002361901,0.000152183,0.0004896338,0.00007846714,0.0000238082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002068462,"about_ca_system_score_gemma":0.00001121277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002486358,"about_ca_topic_score_gemma":0.000001386369,"domain_scores_codex":[0.9986889,0.00004695231,0.0002690162,0.0003711921,0.0002540545,0.0003698438],"domain_scores_gemma":[0.9996328,0.00001274724,0.00008427586,0.0001437265,0.00000398724,0.0001224839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001173003,0.003037502,0.4794097,0.001760611,0.001230014,0.0006870019,0.01516173,0.0005361686,0.003607091,0.0758164,0.00250422,0.4150766],"study_design_scores_gemma":[0.00451762,0.0007765337,0.3604965,0.00002880789,0.0001855643,0.00006307074,0.1030385,0.0003857915,0.01183851,0.006696292,0.5106711,0.001301771],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860051,0.00362086,0.0003387367,0.00006004345,0.00009887543,0.0003623406,0.000002932916,0.00002793714,0.009483194],"genre_scores_gemma":[0.9864084,0.0006373633,0.001524776,0.00005810781,0.00002263434,0.0000247167,0.00008220975,0.00001246276,0.01122935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5081668,"threshold_uncertainty_score":0.7121444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007436809005079336,"score_gpt":0.1787961378269089,"score_spread":0.1713593288218296,"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."}}