{"id":"W4399436263","doi":"10.1016/b978-0-323-99738-6.00004-6","title":"Conveying bioenergy","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cape Breton University","funders":"","keywords":"Bioenergy; Environmental science; Renewable energy; Biology; Ecology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005624433,0.0003853242,0.0003431258,0.0001223649,0.00005540354,0.00003970448,0.0001642861,0.0002123411,0.0001024686],"category_scores_gemma":[0.000002750097,0.0003826304,0.0001732451,0.00001063173,0.00004638356,0.00002997206,0.00008787818,0.0006246963,0.0005748195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006750701,"about_ca_system_score_gemma":0.00001287086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.782856e-8,"about_ca_topic_score_gemma":0.000001354152,"domain_scores_codex":[0.9990155,0.000003277355,0.0002861163,0.00030032,0.0001333948,0.000261378],"domain_scores_gemma":[0.999552,0.00004394219,0.00003642299,0.0002599347,0.00001881498,0.000088942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001518535,3.493031e-7,3.249385e-8,0.0002139943,0.0000708074,0.0001371177,0.00004685967,0.000557743,0.001055075,0.01518064,0.00008717987,0.9826487],"study_design_scores_gemma":[0.00005408593,0.00001300309,7.859748e-8,0.0006506878,0.00004991836,0.0000325037,0.000002066967,0.0004624275,0.003989489,0.01903152,0.9752957,0.0004184965],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00008337964,0.00536819,0.00003160879,0.00000863966,0.001649303,0.0001272013,0.00001213622,0.0008860049,0.9918335],"genre_scores_gemma":[0.004895895,0.0001510441,0.0001481122,0.0000924253,0.0007293162,0.000007870132,0.00001132555,0.0002015871,0.9937624],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9822302,"threshold_uncertainty_score":0.9998626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159025541821141,"score_gpt":0.2226842715984001,"score_spread":0.206781717416286,"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."}}