{"id":"W1517260168","doi":"10.1007/s10198-009-0179-9","title":"Copayments for Ambulatory Care in Germany: A Natural Experiment Using a Difference-in-Difference Approach","year":2008,"lang":"en","type":"preprint","venue":"The European Journal of Health Economics","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Copayment; Natural experiment; Health insurance; Ambulatory; Difference in differences; Quarter (Canadian coin); Medicine; Health care; Government (linguistics); Private insurance; Health economics; Ambulatory care; Family medicine; Public health; Economics; Nursing","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":[0.007607442,0.0007943446,0.001105554,0.0005713846,0.0009171217,0.001770746,0.001026117,0.002900502,0.002994575],"category_scores_gemma":[0.02141341,0.0004513958,0.001045163,0.0007673454,0.001342619,0.001351307,0.0008680215,0.00154212,0.000418646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002182301,"about_ca_system_score_gemma":0.001344588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01757393,"about_ca_topic_score_gemma":0.01050906,"domain_scores_codex":[0.9962754,0.002401234,0.0001762608,0.0004313966,0.0002271038,0.0004886188],"domain_scores_gemma":[0.9777316,0.01513859,0.0032161,0.002156892,0.0003848993,0.00137195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.1363701,0.07954267,0.3485194,0.001710403,0.006319549,0.001646958,0.007034299,0.2453886,0.0135931,0.0684576,0.02313201,0.06828533],"study_design_scores_gemma":[0.01774539,0.04467788,0.6503072,0.0001717766,0.002840704,0.0003095759,0.003597346,0.2529459,0.005600078,0.01480496,0.006402049,0.000597157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983466,0.00008595735,0.0005807992,0.0001980846,0.00002997962,0.00006419406,0.0004005239,0.00001754822,0.0002762077],"genre_scores_gemma":[0.9980007,0.00005581696,0.0007328466,0.0000534346,0.00002071856,0.000114406,0.0004377959,0.000004175877,0.0005801608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01757393,"threshold_uncertainty_score":0.04023248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1427818948731164,"score_gpt":0.3178890316982406,"score_spread":0.1751071368251242,"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."}}