{"id":"W3091469317","doi":"10.3390/electronics9101613","title":"IoT System for School Dropout Prediction Using Machine Learning Techniques Based on Socioeconomic Data","year":2020,"lang":"en","type":"article","venue":"Electronics","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; King Saud University","keywords":"Machine learning; Dropout (neural networks); Computer science; Artificial intelligence; Decision tree; Support vector machine; Context (archaeology); Precision and recall; Multilayer perceptron; Process (computing); Naive Bayes classifier; Socioeconomic status; Modalities; Artificial neural network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003448146,0.0007841013,0.0008239512,0.001587343,0.0003307475,0.0006442911,0.0006896694,0.0005817802,0.001943009],"category_scores_gemma":[0.0009842624,0.0001901076,0.0005626233,0.0008496325,0.00009803562,0.0006575243,0.0006341212,0.0004920961,0.001433022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003294591,"about_ca_system_score_gemma":0.0003410465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003057373,"about_ca_topic_score_gemma":0.003068219,"domain_scores_codex":[0.9996794,0.00003057217,0.00005835038,0.00009613711,0.00009083348,0.00004463761],"domain_scores_gemma":[0.9996741,0.00007037543,0.00007098775,0.00004032912,0.0001081604,0.00003593664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001249928,0.001690855,0.1838748,0.0008155008,0.000385374,0.00268481,0.0003718032,0.06387237,0.02047262,0.001903989,0.04114769,0.6815302],"study_design_scores_gemma":[0.00006974274,0.0004000215,0.05239133,0.0001309988,0.0001421369,0.0004814508,0.0002160596,0.9213281,0.01368819,0.002514514,0.008561455,0.00007599437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5892634,0.002165435,0.3228841,0.002032847,0.001174799,0.0008770243,0.01890412,0.03709874,0.02559963],"genre_scores_gemma":[0.9472702,0.0006636098,0.03809639,0.0002844908,0.0001378832,0.0003935969,0.007839334,0.00009538623,0.005219068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003057373,"threshold_uncertainty_score":0.006500065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0265834733912835,"score_gpt":0.2824811232976079,"score_spread":0.2558976499063244,"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."}}