{"id":"W4406349402","doi":"10.3390/insects16010077","title":"Macronutrient-Based Predictive Modelling of Bioconversion Efficiency in Black Soldier Fly Larvae (Hermetia illucens) Through Artificial Substrates","year":2025,"lang":"en","type":"article","venue":"Insects","topic":"Insect Utilization and Effects","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Hermetia illucens; Bioconversion; Dry matter; Biology; Factorial experiment; Food science; Larva; Composition (language); Fractional factorial design; Pellet; Response surface methodology; Biotechnology; Animal science; Botany; Chromatography; Ecology; Chemistry; Mathematics; Fermentation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002596138,0.0005096292,0.0003438319,0.0002033481,0.0001395641,0.0007328993,0.0002954606,0.0003714177,0.0003254414],"category_scores_gemma":[0.0003472927,0.000180135,0.0004042508,0.0001631813,0.0001740403,0.0002417313,0.0001988757,0.0002445001,0.00006813651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005708073,"about_ca_system_score_gemma":0.0003482463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01227807,"about_ca_topic_score_gemma":0.009198721,"domain_scores_codex":[0.9999468,0.00001315854,0.000004063487,0.00001627832,0.0000111932,0.00000844926],"domain_scores_gemma":[0.9998708,0.00007827414,0.00002524994,0.000005160957,0.00001514938,0.000005378064],"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":[0.0001192846,0.00006929899,0.005268064,0.0001070162,0.00003396015,0.00005180512,0.00002323493,0.974212,0.01485769,0.0002284749,0.00004135447,0.004987871],"study_design_scores_gemma":[0.000004216859,0.00006994039,0.002204938,0.000003896685,0.0000113274,0.000005735677,0.000009208341,0.9951833,0.002393581,0.00004623845,0.00006370107,0.000003903492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854724,0.0004061675,0.01293012,0.00002547346,0.000005685095,0.00001677455,0.000123449,0.00003212482,0.0009879734],"genre_scores_gemma":[0.9974625,0.000190235,0.002032814,0.000003599818,9.123823e-7,0.00001796916,0.00005624864,0.00000353037,0.000232155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01227807,"threshold_uncertainty_score":0.02441323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729678847349686,"score_gpt":0.2306896809937174,"score_spread":0.2033928925202206,"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."}}