{"id":"W2186453867","doi":"","title":"Richer Connections to Robotics through Project Personalization","year":2012,"lang":"en","type":"article","venue":"AEE Journal","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Robotics; Outreach; Creativity; Artificial intelligence; Educational robotics; Computer Science and Engineering; Robot; Personalization; Exhibition; Computer science; Psychology; Software engineering; World Wide Web; Visual arts; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005692332,0.00007020585,0.00006982002,0.00007294014,0.000409886,0.0002626356,0.0002428774,0.00003461281,0.00001262394],"category_scores_gemma":[0.0001432229,0.00005965773,0.0000484807,0.0003239897,0.000008884169,0.0006800253,0.00005387375,0.0003120181,0.00007077237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005824475,"about_ca_system_score_gemma":0.00005087026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000292409,"about_ca_topic_score_gemma":0.000002101148,"domain_scores_codex":[0.9991738,0.0001292207,0.0001239401,0.00009558532,0.000193881,0.0002836227],"domain_scores_gemma":[0.9995888,0.00004572034,0.00007311492,0.0001295335,0.00006350331,0.00009925457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001502245,0.0006736311,0.09931933,0.00003451011,0.0001750734,0.00002879089,0.2094434,0.01958377,0.0004604885,0.1500548,0.07488405,0.4453272],"study_design_scores_gemma":[0.0003017026,0.000197338,0.01162916,0.00005494186,0.00002374402,0.001369644,0.001137868,0.005009197,0.00005758918,0.000376909,0.9795364,0.0003055293],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006492528,0.000208121,0.9887684,0.002624381,0.0009697085,0.00005585775,9.389028e-8,0.0001124046,0.0007685322],"genre_scores_gemma":[0.5960081,0.000006942113,0.4020754,0.0005406462,0.0005840892,0.000002810862,4.105986e-7,0.000008501295,0.0007730575],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9046523,"threshold_uncertainty_score":0.3152553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05802176851525104,"score_gpt":0.3303870997259815,"score_spread":0.2723653312107304,"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."}}