{"id":"W3088303759","doi":"10.1145/3402942.3403000","title":"Effect of Timer, Top Score and Leaderboard on Performance and Motivation in a Human Computing Game","year":2020,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Timer; Computer science; Game mechanics; Outcome (game theory); Video game; Human–computer interaction; Quality (philosophy); Multimedia; Mathematical economics; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002024406,0.00007744177,0.0001341372,0.0000548749,0.00003285335,0.00003521016,0.0001530364,0.0000285,0.000003630653],"category_scores_gemma":[0.00006550683,0.00006436788,0.00001128078,0.0001843207,0.00006775961,0.0001859888,0.00009356817,0.00008864182,0.000004524143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006498964,"about_ca_system_score_gemma":0.000006218228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003005196,"about_ca_topic_score_gemma":0.000003348528,"domain_scores_codex":[0.999346,0.00004809006,0.0001685005,0.0002200679,0.000108125,0.0001092099],"domain_scores_gemma":[0.9995957,0.0001972807,0.00004897462,0.0001032019,0.00001645873,0.00003835394],"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":[0.0000524009,0.00003841201,0.4435327,0.0003014578,0.00000911488,0.000005985746,0.01260469,0.003056336,0.01977459,0.01261653,0.00007520014,0.5079326],"study_design_scores_gemma":[0.0001386324,0.001182007,0.04061279,0.0001048854,0.000001754092,0.000001553621,0.00005025326,0.7153175,0.2423579,0.0001112529,0.00002134975,0.0001000917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802271,0.00002287785,0.01847448,0.0004384039,0.0000227165,0.0001292977,7.972794e-8,0.00004011452,0.0006449482],"genre_scores_gemma":[0.9988026,0.000005465665,0.0009384139,0.0002120265,0.00002046247,0.000001188201,2.250129e-7,0.000003263441,0.00001633713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7122612,"threshold_uncertainty_score":0.2624846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04518418263136691,"score_gpt":0.289585936037855,"score_spread":0.2444017534064881,"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."}}