{"id":"W7097576705","doi":"","title":"Evaluating search and matching models using experimental data”, mimeo","year":2005,"lang":"en","type":"article","venue":"","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Earnings; Randomized experiment; Measure (data warehouse); Test (biology); Quasi-experiment; Constant (computer programming); Corporation; Control (management)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05560762,0.001126434,0.001571997,0.00163549,0.001161901,0.002500561,0.002653395,0.002545094,0.01548423],"category_scores_gemma":[0.1633919,0.001021029,0.001961282,0.002293573,0.002648894,0.003412193,0.001919765,0.00213046,0.00186479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003529909,"about_ca_system_score_gemma":0.001815455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007810813,"about_ca_topic_score_gemma":0.006696888,"domain_scores_codex":[0.9802304,0.01722087,0.0005061335,0.0008578273,0.0009274895,0.0002573392],"domain_scores_gemma":[0.6925511,0.2833758,0.006267989,0.01333373,0.003532782,0.0009385995],"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":[0.004002036,0.003384386,0.04552064,0.001525734,0.003882603,0.0005581883,0.001147915,0.4979401,0.001399662,0.2242929,0.07951427,0.1368316],"study_design_scores_gemma":[0.001085539,0.001261724,0.01298248,0.0001085141,0.000398239,0.00009114161,0.0003791941,0.8318546,0.001477196,0.1365241,0.01371002,0.0001271889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4425575,0.005162869,0.4906164,0.01669113,0.002852835,0.002315369,0.007734065,0.001583708,0.03048622],"genre_scores_gemma":[0.8197395,0.002613629,0.15761,0.002307255,0.0008015198,0.004148215,0.003958468,0.0003305091,0.00849096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05560762,"threshold_uncertainty_score":0.2940847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4532770094041289,"score_gpt":0.3997619628980919,"score_spread":0.053515046506037,"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."}}