{"id":"W2151101070","doi":"10.2139/ssrn.789464","title":"Evaluating Search and Matching Models Using Experimental Data","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Matching (statistics); Computer science; Data mining; Econometrics; Mathematics; Statistics","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":[0.03319387,0.001594028,0.001658682,0.002982654,0.0009161326,0.003021617,0.002526994,0.004884963,0.005886903],"category_scores_gemma":[0.2606556,0.0008813723,0.00122072,0.003074117,0.001793078,0.006159685,0.001365516,0.001959367,0.00173516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003281186,"about_ca_system_score_gemma":0.002476987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005069088,"about_ca_topic_score_gemma":0.003744588,"domain_scores_codex":[0.9827508,0.01354601,0.001007566,0.001318539,0.00104065,0.0003363888],"domain_scores_gemma":[0.4876653,0.4844159,0.007455796,0.01436469,0.005066705,0.001031626],"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":[0.009979248,0.004061622,0.04224704,0.001184764,0.001338232,0.0001551069,0.0003678813,0.8067759,0.001839558,0.02417662,0.005198864,0.1026752],"study_design_scores_gemma":[0.0007049862,0.001112048,0.002516879,0.00004540744,0.0002025836,0.00005769053,0.00010957,0.9731599,0.001774237,0.01971672,0.0005629526,0.00003700982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9202089,0.001520539,0.07100625,0.001290142,0.0001375891,0.0003833534,0.001361828,0.0004567646,0.003634576],"genre_scores_gemma":[0.9701605,0.0003035942,0.02567771,0.0001610525,0.00006448186,0.0003407266,0.002255848,0.00007840789,0.0009576106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03319387,"threshold_uncertainty_score":0.1755481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.46222288934752,"score_gpt":0.568678542894699,"score_spread":0.106455653547179,"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."}}