{"id":"W3106661256","doi":"10.3390/math8122101","title":"Estimating the Academic Performance of Secondary Education Mathematics Students: A Gain Lift Predictive Model","year":2020,"lang":"en","type":"article","venue":"Mathematics","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Socioeconomic status; Mathematics education; Competence (human resources); Quarter (Canadian coin); Lift (data mining); Ethnic group; Academic achievement; Psychology; Mathematics; Computer science; Social psychology; Medicine; Geography","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":[0.004175656,0.0009362636,0.0007836157,0.001966316,0.0004788988,0.001618833,0.001370882,0.0008715708,0.002155981],"category_scores_gemma":[0.006890614,0.0004042173,0.001252856,0.0008224044,0.0005920412,0.0006109093,0.001486426,0.001747656,0.0006018411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008825075,"about_ca_system_score_gemma":0.001732061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01318634,"about_ca_topic_score_gemma":0.005765993,"domain_scores_codex":[0.9990018,0.0004003307,0.0000566945,0.000202193,0.000193284,0.0001456715],"domain_scores_gemma":[0.9962374,0.002669173,0.0002540427,0.0001784906,0.0004933216,0.0001675603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008772644,0.001515271,0.6337302,0.000085766,0.000419585,0.0003375104,0.0003928011,0.2796816,0.001133962,0.001720848,0.00149578,0.07860954],"study_design_scores_gemma":[0.00002869535,0.0002763056,0.06009948,0.00003404545,0.00007506215,0.00006856677,0.0001669006,0.9374954,0.0002721737,0.001185262,0.0002810977,0.00001709521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583235,0.0001496549,0.03882745,0.0003211061,0.00003070707,0.000194105,0.0004560043,0.0001618577,0.001535517],"genre_scores_gemma":[0.9930525,0.00007607595,0.005563593,0.0000158855,0.00001214752,0.00009087212,0.0004538909,0.000008970193,0.0007260083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01318634,"threshold_uncertainty_score":0.02621919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03956022899323365,"score_gpt":0.3268701471064749,"score_spread":0.2873099181132413,"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."}}