{"id":"W7100325569","doi":"","title":"Evaluating Search and Matching Models Using Experimental Data.” Unpublished manuscript","year":2005,"lang":"en","type":"article","venue":"","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and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; Test (biology); Measure (data warehouse); Corporation; Control (management); Constant (computer programming)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002558141,0.0001235442,0.0002513549,0.0001357438,0.0001790161,0.0002898738,0.0003124593,0.00005756678,0.0003465038],"category_scores_gemma":[0.00003279599,0.0001350444,0.00002727584,0.0000941082,0.00003663083,0.001478048,0.0003104381,0.0001241474,0.0000837589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007344773,"about_ca_system_score_gemma":0.00001196617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007477407,"about_ca_topic_score_gemma":0.00001345313,"domain_scores_codex":[0.9986782,0.00004525228,0.0004638819,0.000478967,0.00005268756,0.0002810195],"domain_scores_gemma":[0.99929,0.00004192757,0.000101682,0.0004732738,0.00001539155,0.00007768438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003527834,0.0001624852,0.003224142,0.00007683039,0.00008475275,0.000002935848,0.007441525,0.06163457,0.004188554,0.9193549,0.0003054746,0.003488522],"study_design_scores_gemma":[0.0004244378,0.00002542596,0.00008601986,0.00002008715,0.000002922852,0.00001767786,0.001488763,0.9860418,0.0005399447,0.01083608,0.0003193921,0.0001974277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654069,0.001421358,0.01638205,0.0001615012,0.0001812806,0.0001535766,0.00003447062,0.00005620404,0.01620264],"genre_scores_gemma":[0.9789925,0.000005436589,0.01926912,0.0001589456,0.0002053254,0.000003373522,0.00001302992,0.00002261499,0.001329657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9244072,"threshold_uncertainty_score":0.5506949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4145539762019931,"score_gpt":0.3753359110431829,"score_spread":0.03921806515881027,"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."}}