{"id":"W1980655759","doi":"10.1007/s11518-006-0152-4","title":"Group size and parallelism effects in tasks with heterogeneous levels of difficulty: A stochastic order approach","year":2004,"lang":"en","type":"article","venue":"Journal of Systems Science and Systems Engineering","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Task (project management); Group (periodic table); Parallelism (grammar); Order (exchange); Computer science; Stochastic ordering; Theoretical computer science; Cognitive psychology; Mathematics; Psychology; Parallel computing; Statistics; Engineering; 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":[0.0074232,0.001108741,0.002570199,0.001433839,0.0009781981,0.002015609,0.001930313,0.002166545,0.007014768],"category_scores_gemma":[0.04259975,0.001358055,0.001480953,0.0007363973,0.002538801,0.003848596,0.002333329,0.002561097,0.0003920283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001723055,"about_ca_system_score_gemma":0.001822914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004430662,"about_ca_topic_score_gemma":0.005601538,"domain_scores_codex":[0.99706,0.001190102,0.0001128388,0.0003692041,0.0006114375,0.0006564561],"domain_scores_gemma":[0.9007438,0.08194172,0.005696245,0.005688728,0.002878672,0.003050874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00202421,0.001273356,0.01173267,0.0002734403,0.0004065696,0.0004920295,0.00116164,0.7238946,0.0133587,0.2175472,0.001730563,0.02610498],"study_design_scores_gemma":[0.0002502985,0.0003952361,0.009559416,0.00001922546,0.0001768037,0.00008010137,0.0001783237,0.8391783,0.001168366,0.1485424,0.0003775277,0.00007398534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6794425,0.0002845675,0.3111151,0.001129125,0.00007960397,0.0002068231,0.0001465798,0.0001841214,0.007411621],"genre_scores_gemma":[0.9799358,0.0001185415,0.01569437,0.0001038707,0.00008442128,0.0001125892,0.00004774631,0.00008037809,0.003822212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0074232,"threshold_uncertainty_score":0.03925812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03248800363734389,"score_gpt":0.2780381477584098,"score_spread":0.245550144121066,"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."}}