{"id":"W3177120446","doi":"","title":"Can Competition Though Leaderboards Lead to Better Engagement and Learning of Data Science Concepts? An Experimental Study","year":2021,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Polytechnique Montréal","funders":"","keywords":"Competition (biology); Lead (geology); Computer science; Industrial organization; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003632492,0.0007530635,0.0007400781,0.0004023621,0.0006669966,0.001561189,0.0008333903,0.001034403,0.00829119],"category_scores_gemma":[0.01295859,0.000483927,0.0004200716,0.0002531151,0.001148578,0.0009812635,0.001284328,0.001852968,0.0007993497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003039977,"about_ca_system_score_gemma":0.0006350378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003721269,"about_ca_topic_score_gemma":0.0004433763,"domain_scores_codex":[0.9981921,0.0007479821,0.0001206439,0.0003986771,0.0002390896,0.0003015371],"domain_scores_gemma":[0.9860113,0.009165387,0.001328985,0.0008734812,0.0003767191,0.002244129],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"nonrandomized_trial","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.04849136,0.6533644,0.05092343,0.00124068,0.0003379245,0.0008569196,0.01798178,0.001978985,0.0825744,0.003285999,0.0017865,0.1371776],"study_design_scores_gemma":[0.01627118,0.5925387,0.2838901,0.0002755391,0.0005566424,0.0004687457,0.009710632,0.009688866,0.06842018,0.005566164,0.01236223,0.0002509692],"study_design_candidate":"nonrandomized_trial","study_design_consensus":"nonrandomized_trial","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998998,0.00001287989,0.0001866541,0.00003447101,0.00001541045,0.0001231361,0.00001696505,0.000007636296,0.000604846],"genre_scores_gemma":[0.994466,0.00006873495,0.002400968,0.00008111889,0.00004261777,0.0007021299,0.00006966366,0.0000115149,0.002157355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9963675,"threshold_uncertainty_score":0.02773678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153861151237212,"score_gpt":0.3544402200404896,"score_spread":0.2390541049167684,"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."}}