{"id":"W2756273103","doi":"10.1145/3123766","title":"Incentives and Gamification","year":2017,"lang":"en","type":"article","venue":"XRDS Crossroads The ACM Magazine for Students","topic":"Educational Games and Gamification","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Israel Academy of Sciences and Humanities","keywords":"Hebrew; Citation; Incentive; Library science; Computer science; History; Classics; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.002427658,0.001172281,0.0007929081,0.001406703,0.001253671,0.00540109,0.001114851,0.003988551,0.05356013],"category_scores_gemma":[0.02061718,0.0003010271,0.0005398534,0.0009471668,0.002974512,0.004375439,0.001727062,0.004715215,0.008585173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001813871,"about_ca_system_score_gemma":0.001861539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001175597,"about_ca_topic_score_gemma":0.002246474,"domain_scores_codex":[0.9984316,0.0006099382,0.00006608222,0.0001622004,0.0005763895,0.0001537009],"domain_scores_gemma":[0.9876935,0.008940656,0.000394986,0.0003340807,0.001649487,0.0009872671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004346062,0.000020149,0.0001091682,0.000198828,0.00001049082,0.00005070229,0.0001504281,0.0001571933,0.00002900872,0.04220718,0.9248993,0.03212422],"study_design_scores_gemma":[0.00002769583,0.00002374795,0.0005344014,0.0006890307,0.00001555008,0.00006714775,0.0002847256,0.0003356638,0.00008828879,0.06415878,0.933758,0.00001696006],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002561189,0.1261785,0.005571278,0.3647012,0.3145072,0.00008411882,0.0005059056,0.0003932005,0.1854974],"genre_scores_gemma":[0.09723752,0.1331377,0.003409297,0.05593731,0.3911664,0.0004358662,0.0005008496,0.0006607105,0.3175142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05356013,"threshold_uncertainty_score":0.1791765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05180303710280908,"score_gpt":0.4481360201131945,"score_spread":0.3963329830103854,"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."}}