{"id":"W1690982000","doi":"","title":"Something to Prove: Reputation in Teams and Hiring to Introduce Uncertainty","year":2004,"lang":"en","type":"article","venue":"The Faculty Digital Archive (New York University)","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Reputation; Commit; Incentive; Work (physics); Business; Microeconomics; Mechanism (biology); Economics; Computer science; Engineering; Political science; Law","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":[0.007753816,0.0003771197,0.0006326392,0.0005518763,0.002067244,0.004270699,0.0009824281,0.00374251,0.01139307],"category_scores_gemma":[0.03939682,0.0003389426,0.0008342337,0.0007166676,0.005418205,0.006575163,0.00243962,0.00293347,0.000689037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001699495,"about_ca_system_score_gemma":0.001015772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001133047,"about_ca_topic_score_gemma":0.0008169256,"domain_scores_codex":[0.9949074,0.003219854,0.0001559347,0.0005310006,0.0006735151,0.0005122059],"domain_scores_gemma":[0.9567835,0.02765087,0.007555898,0.005062506,0.001228711,0.001718514],"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":[0.0001631897,0.0002092402,0.005604621,0.0001056244,0.00007953777,0.0003191969,0.001621838,0.008180466,0.0008982071,0.956418,0.003942499,0.02245749],"study_design_scores_gemma":[0.0001202448,0.0001694659,0.003521348,0.00007256946,0.00005801284,0.0002212021,0.0007433047,0.01693058,0.0006917271,0.969968,0.007456851,0.0000467415],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4616553,0.002736916,0.2795211,0.05266064,0.001282598,0.000183041,0.0003110198,0.0003215982,0.2013278],"genre_scores_gemma":[0.9828896,0.0004830059,0.009054801,0.001039679,0.0002925687,0.00007018273,0.00002042239,0.00002605779,0.006123575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01139307,"threshold_uncertainty_score":0.04100662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02981140355832251,"score_gpt":0.2844621312836561,"score_spread":0.2546507277253335,"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."}}