{"id":"W4205624697","doi":"10.2139/ssrn.3879348","title":"Search, Screening and Sorting","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sorting; Computer science; Medicine; Algorithm","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":[0.002767306,0.0007846854,0.001900604,0.007670588,0.003015665,0.004951804,0.001767539,0.002108289,0.07663343],"category_scores_gemma":[0.02340935,0.0009025064,0.001599108,0.00744364,0.0009603675,0.004090995,0.002453106,0.0009588316,0.03521978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284818,"about_ca_system_score_gemma":0.005338083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009910155,"about_ca_topic_score_gemma":0.01564645,"domain_scores_codex":[0.9952996,0.001502283,0.0004059274,0.0006648228,0.001458868,0.0006684556],"domain_scores_gemma":[0.9878106,0.005837357,0.0005212009,0.003592449,0.001639776,0.0005986716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001565544,0.0008078889,0.01489707,0.0003871756,0.0001181899,0.0003969209,0.0005385503,0.004058085,0.00685741,0.04066051,0.08005488,0.8496577],"study_design_scores_gemma":[0.0007842227,0.002229014,0.0581758,0.0004439567,0.0007063351,0.005706738,0.004291196,0.2427898,0.04513696,0.3083687,0.3308784,0.0004888456],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2696694,0.003512707,0.4173855,0.006053032,0.001225204,0.004260583,0.01545999,0.02153746,0.2608962],"genre_scores_gemma":[0.5470823,0.001102465,0.2207943,0.001027143,0.0003868449,0.0008355117,0.0110777,0.001213312,0.2164805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07663343,"threshold_uncertainty_score":0.2563643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178700292578005,"score_gpt":0.2456786950988062,"score_spread":0.2278086658410058,"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."}}