{"id":"W2883291320","doi":"10.69520/jipe.v1i1.37","title":"Learning Code using Lego Robotics","year":2018,"lang":"en","type":"article","venue":"Journal of innovation in polytechnic education.","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Humber Polytechnic","funders":"","keywords":"Artificial intelligence; Robotics; Code (set theory); Computer science; Computer vision; Programming language; Robot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004103487,0.0005680226,0.000237594,0.0003968178,0.0004327424,0.001169242,0.0005463705,0.0005017957,0.01819451],"category_scores_gemma":[0.002239716,0.0001128737,0.0003178762,0.0001767205,0.0006135593,0.0009848478,0.001487541,0.0008003543,0.003943653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005178329,"about_ca_system_score_gemma":0.00109641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000891613,"about_ca_topic_score_gemma":0.003444632,"domain_scores_codex":[0.9996712,0.00006675026,0.00001304355,0.00005645992,0.0001207291,0.00007189176],"domain_scores_gemma":[0.9993196,0.0002333084,0.00009472994,0.00005907258,0.0001023531,0.0001909924],"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":[0.0005246436,0.00864843,0.03923437,0.001638123,0.00004362315,0.001072354,0.02340596,0.003591256,0.05206075,0.04032333,0.05716781,0.7722895],"study_design_scores_gemma":[0.0002683796,0.009799809,0.08186556,0.001506601,0.00007815134,0.002867098,0.01366627,0.01773416,0.0431715,0.06208348,0.7667238,0.0002351537],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7468596,0.0006471915,0.07161892,0.002372483,0.0002431342,0.001085158,0.0008000457,0.002359156,0.1740144],"genre_scores_gemma":[0.7770243,0.001264091,0.1276219,0.002393454,0.00006046093,0.001708532,0.001293555,0.000238738,0.08839496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01819451,"threshold_uncertainty_score":0.06086665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03203278282737169,"score_gpt":0.336686578811268,"score_spread":0.3046537959838963,"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."}}