{"id":"W4415359962","doi":"10.59934/jaiea.v5i1.1489","title":"Application of the K-Means Clustering Method to Cluster Stunting Cases Based on Family Economics in Langkat Regency","year":2025,"lang":"","type":"article","venue":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Cluster analysis; Cluster (spacecraft); Quality (philosophy); Process (computing); Euclidean distance; Developing country","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":[0.002067567,0.0005469681,0.0007216381,0.00463501,0.001162295,0.001205957,0.0009859763,0.0006288008,0.001824619],"category_scores_gemma":[0.005171375,0.0002940939,0.001028876,0.003057062,0.0004320621,0.0003432152,0.001008361,0.0005626997,0.0003182473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375786,"about_ca_system_score_gemma":0.002509246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04286991,"about_ca_topic_score_gemma":0.05032743,"domain_scores_codex":[0.9989843,0.0003107192,0.000174061,0.0002187845,0.0002008614,0.0001111541],"domain_scores_gemma":[0.9982856,0.0007485177,0.0002544009,0.0001399047,0.000482552,0.00008893816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001106822,0.001089248,0.4094597,0.001288138,0.000799623,0.003220762,0.01072129,0.1177318,0.00733605,0.00487984,0.01211518,0.4302515],"study_design_scores_gemma":[0.0001025021,0.0003248995,0.3592618,0.0003860379,0.0002997102,0.0007997556,0.01398215,0.598312,0.007263062,0.008433021,0.01062599,0.0002091159],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8453828,0.000464484,0.1431662,0.0005154521,0.0001131838,0.00175316,0.002453458,0.0009650232,0.005186271],"genre_scores_gemma":[0.7903252,0.000263594,0.2040349,0.00003276698,0.00001758603,0.000976923,0.002411386,0.00007366161,0.001863938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04286991,"threshold_uncertainty_score":0.08524078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02508013874655966,"score_gpt":0.3070625887070044,"score_spread":0.2819824499604447,"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."}}