{"id":"W2891325114","doi":"10.3386/w25068","title":"When does Product Liability Risk Chill Innovation? Evidence from Medical Implants","year":2018,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Liability; Business; Product liability; Product (mathematics); Actuarial science; Monetary economics; Economics; Finance; Mathematics","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":[0.02695181,0.0005630074,0.001065504,0.003660239,0.001266005,0.005761798,0.002226328,0.006721649,0.03020984],"category_scores_gemma":[0.2246815,0.000462784,0.002548532,0.002924405,0.004033932,0.004926786,0.002715942,0.005394314,0.00291979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002072702,"about_ca_system_score_gemma":0.004335962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008660988,"about_ca_topic_score_gemma":0.01080358,"domain_scores_codex":[0.9748258,0.009951954,0.002502686,0.001869551,0.009030559,0.001819531],"domain_scores_gemma":[0.5391583,0.3779635,0.05574445,0.01123937,0.01220001,0.003694254],"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":[0.01492192,0.001996633,0.3234087,0.01181443,0.004680674,0.002916486,0.004460315,0.001854898,0.0006450572,0.1483754,0.1012725,0.3836531],"study_design_scores_gemma":[0.004494987,0.006701508,0.4016605,0.03144602,0.01417914,0.005454272,0.007305729,0.001927671,0.003257447,0.2176668,0.3055423,0.0003634919],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2295949,0.3590129,0.005529894,0.1502925,0.001215553,0.0004317435,0.007865846,0.0001115587,0.2459451],"genre_scores_gemma":[0.8615744,0.09981687,0.001199039,0.02104557,0.002496329,0.0001406059,0.001861619,0.00005026213,0.01181526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03020984,"threshold_uncertainty_score":0.1425365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5655042336249827,"score_gpt":0.6538764752651509,"score_spread":0.08837224164016821,"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."}}