{"id":"W4410241975","doi":"10.18280/mmep.120431","title":"Performance Evaluation and Optimization of a Palm Kernel Cracker – A Taguchi-Grey Relational Analysis Approach","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grey relational analysis; Taguchi methods; Palm; Kernel (algebra); Palm kernel; Computer science; Artificial intelligence; Mathematics; Statistics; Palm oil; Machine learning; Chemistry; Food science; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001954602,0.0006911179,0.001193288,0.0007570992,0.0002835758,0.001034501,0.0007257177,0.0007484476,0.0006705569],"category_scores_gemma":[0.001603302,0.0003786031,0.00105597,0.0008696885,0.000294127,0.0005743015,0.0004031982,0.0004787952,0.0002699487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006696003,"about_ca_system_score_gemma":0.0006400348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600387,"about_ca_topic_score_gemma":0.002541488,"domain_scores_codex":[0.9985095,0.0003783464,0.0001076773,0.0002134661,0.000715919,0.00007498071],"domain_scores_gemma":[0.9995409,0.0002031702,0.00009077224,0.00003344462,0.0001178222,0.00001388013],"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":[0.0004541953,0.0004624831,0.002522981,0.001142372,0.0001327995,0.0001288256,0.0002426882,0.2791227,0.6089082,0.002094342,0.0002331551,0.1045552],"study_design_scores_gemma":[0.00002657437,0.001538183,0.00358607,0.00003186206,0.0001565895,0.00009944848,0.00009064822,0.7257845,0.2666318,0.0005656596,0.001429079,0.00005958075],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3905946,0.001897243,0.6038558,0.0001337649,0.00002788601,0.0002686314,0.0001076382,0.0002814054,0.002833162],"genre_scores_gemma":[0.8552484,0.0008852435,0.1422914,0.00002595358,0.000005543687,0.0001686396,0.00006726255,0.00003137299,0.001276352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001954602,"threshold_uncertainty_score":0.01033705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02531988670629719,"score_gpt":0.2438229630686238,"score_spread":0.2185030763623266,"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."}}