{"id":"W2184441487","doi":"","title":"The Effects of Compensation Schemes on Self-Selection and Work Productivity: An Experimental Investigation","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Guelph","funders":"","keywords":"Compensation (psychology); Productivity; Lottery; Incentive; Selection (genetic algorithm); Task (project management); Work (physics); Piece work; Scheme (mathematics); Econometrics; Salient; Economics; Computer science; Microeconomics; Mathematics; Psychology; Engineering; Social psychology; Artificial intelligence; Management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009589539,0.0000862368,0.00009722441,0.00004402424,0.001091927,0.00006657139,0.00009273082,0.00004093158,6.602762e-7],"category_scores_gemma":[0.00007034151,0.00007122102,0.00002847211,0.0001331067,0.0001976966,0.000343772,0.00001675553,0.0003705418,0.000001502278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449901,"about_ca_system_score_gemma":0.0005694297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004457703,"about_ca_topic_score_gemma":0.002900101,"domain_scores_codex":[0.9988129,0.0001519101,0.0001471314,0.0001430848,0.0001784428,0.0005665341],"domain_scores_gemma":[0.9996306,0.00005838669,0.0001531797,0.00006037086,0.00004556876,0.00005191952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001200104,0.0003442143,0.03084073,0.000006235226,0.00009498123,4.048119e-7,0.02418451,0.00002987776,0.07444783,0.8608446,0.000006737017,0.009079871],"study_design_scores_gemma":[0.002434146,0.004698901,0.01568483,0.0001155759,0.00008038662,0.00003691286,0.04883125,0.00001060466,0.6140876,0.3129585,0.0005561693,0.0005051168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969994,0.001713468,0.00002115242,0.0006240665,0.0001988588,0.0002582679,9.073513e-8,0.00002860234,0.0001561083],"genre_scores_gemma":[0.9986212,0.0009911369,0.0001329961,0.00001742221,0.0001681659,0.00001556274,5.715502e-7,0.000008579523,0.00004432505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5478861,"threshold_uncertainty_score":0.8398331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323873384538448,"score_gpt":0.2886366586650997,"score_spread":0.2753979248197152,"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."}}