{"id":"W4394891968","doi":"10.3390/educsci14040423","title":"Learning Multiplication by Translating across Microworlds","year":2024,"lang":"en","type":"article","venue":"Education Sciences","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Multiplication (music); Mathematics education; Computer science; Arithmetic; Psychology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004354812,0.00007753884,0.00005189735,0.0000727434,0.0007430659,0.0006327606,0.0005656271,0.00002906678,0.000017929],"category_scores_gemma":[0.00002425,0.0000708833,0.00003593992,0.001302539,0.0001245796,0.0009940424,0.00004527372,0.0001190936,0.000141571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003844196,"about_ca_system_score_gemma":0.0003071075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000534766,"about_ca_topic_score_gemma":0.000004296504,"domain_scores_codex":[0.9989315,0.00003540029,0.0001696629,0.0004429046,0.0002177174,0.0002028461],"domain_scores_gemma":[0.9995676,0.0001067996,0.0000415916,0.0001679406,0.00005736666,0.00005866478],"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":[1.649705e-7,0.00009367644,0.0009598406,0.00001618772,0.000004256601,1.532801e-7,0.006931356,0.0003171845,0.0170249,0.1070178,0.009273538,0.858361],"study_design_scores_gemma":[0.00008932567,0.00007635777,0.003778168,0.0001397857,0.00000513498,0.00003291925,0.003148813,0.5378712,0.005379376,0.01849809,0.4305504,0.0004304153],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05080885,0.005919848,0.907268,0.02587598,0.001102312,0.0002459034,0.000005894391,0.0006456319,0.008127593],"genre_scores_gemma":[0.9291519,0.00004067922,0.06734478,0.0001316884,0.0001144747,0.00009593872,0.00001091714,0.000004598095,0.003105039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.878343,"threshold_uncertainty_score":0.6101725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076342889523525,"score_gpt":0.3483114264254637,"score_spread":0.3275479975302285,"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."}}