{"id":"W2910887493","doi":"10.1111/jels.12208","title":"Damage Caps and Defensive Medicine: Reexamination with Patient‐Level Data","year":2019,"lang":"en","type":"article","venue":"Journal of Empirical Legal Studies","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"National Heart, Lung, and Blood Institute","keywords":"Defensive medicine; Medicine; Malpractice; Medical malpractice; Psychological intervention; Medicare Part B; Tort reform; Health care; Liability; Emergency medicine; Finance; Economics; Tort; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001522743,0.0001381013,0.0005680235,0.00008565325,0.0002347433,0.000007729705,0.0002093404,0.00009501416,0.0002301055],"category_scores_gemma":[0.009822261,0.00007281847,0.00002307063,0.0001734008,0.000254357,0.0005868793,0.0003067181,0.0008791005,0.00003949864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007635579,"about_ca_system_score_gemma":0.0001744627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001142127,"about_ca_topic_score_gemma":0.0001261033,"domain_scores_codex":[0.9976265,0.0005407592,0.0007287536,0.00021569,0.0006395679,0.0002487641],"domain_scores_gemma":[0.994075,0.003788406,0.0006633273,0.0003301732,0.0009676194,0.0001754742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008520092,0.0002172062,0.5848407,0.0008133659,0.0005682337,0.0002044518,0.03247902,0.000003518725,0.0001302881,0.0008765767,0.3723386,0.006676098],"study_design_scores_gemma":[0.002244106,0.003071366,0.2850964,0.001318564,0.0002817481,0.00005071897,0.09890399,0.00005690844,0.000007193619,0.0004784261,0.6083044,0.0001861255],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9308533,0.002341686,0.00004447607,0.06198509,0.0006311418,0.0002975537,0.00001256897,0.000009354852,0.003824812],"genre_scores_gemma":[0.9929533,0.000716024,0.0008262186,0.004012406,0.000569226,0.000003451732,0.000006470226,0.00001137679,0.0009015127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2997442,"threshold_uncertainty_score":0.9985184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3288642863183848,"score_gpt":0.5338800208500991,"score_spread":0.2050157345317143,"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."}}