{"id":"W4409780583","doi":"10.55124/jbid.v2i2.247","title":"Predictive Modeling of Process Parameters in WCO-Based Biodiesel Production Using Advanced Regression Techniques","year":2025,"lang":"en","type":"article","venue":"Journal of business intelligence and data analytics.","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biodiesel production; Process engineering; Process (computing); Production (economics); Regression analysis; Regression; Biodiesel; Computer science; Statistics; Mathematics; Engineering; Chemistry; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008424548,0.0007291103,0.0005549261,0.0003808309,0.0002366705,0.000815725,0.0005257562,0.0007332604,0.0007214641],"category_scores_gemma":[0.001706024,0.0004244356,0.0008012945,0.0004701427,0.000311616,0.0005377472,0.0002988261,0.001146329,0.0003161082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006413415,"about_ca_system_score_gemma":0.0006903938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01254249,"about_ca_topic_score_gemma":0.006691935,"domain_scores_codex":[0.9998336,0.00003282574,0.0000111875,0.00005759724,0.00003985412,0.00002500842],"domain_scores_gemma":[0.9993966,0.0004108798,0.00006965575,0.00002921837,0.00008451592,0.000009187569],"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":[0.00006595288,0.00005139081,0.001915847,0.00005278948,0.00001814997,0.00004098819,0.00003059379,0.9840232,0.005118639,0.0004630701,0.00008724032,0.008132115],"study_design_scores_gemma":[0.000001505232,0.00001106823,0.0001943301,0.000001630355,0.000002313436,0.000002381706,0.000002828352,0.998412,0.001246123,0.00006597186,0.00005746156,0.000002446656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6594763,0.00099349,0.3338065,0.0003305986,0.00005041212,0.0001082041,0.0005549466,0.001149784,0.003529745],"genre_scores_gemma":[0.9860356,0.0003680673,0.01226155,0.00001668492,0.000005912946,0.00007378488,0.000210219,0.00002960593,0.0009986717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01254249,"threshold_uncertainty_score":0.02493894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05245325914960842,"score_gpt":0.3264384801370338,"score_spread":0.2739852209874254,"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."}}