{"id":"W2005455137","doi":"10.1016/j.jhealeco.2011.08.005","title":"A nonparametric vs. latent class model of general practitioner utilization: Evidence from Canada","year":2011,"lang":"en","type":"article","venue":"Journal of Health Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Econometrics; Estimator; Negative binomial distribution; Statistics; Mathematics; Conditional probability distribution; Latent class model; Count data; Nonparametric statistics; Kernel density estimation; Poisson distribution","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01986334,0.001027755,0.001847078,0.001951228,0.002858208,0.00546531,0.005038819,0.002183588,0.006385718],"category_scores_gemma":[0.04999362,0.0007930139,0.003199637,0.004280956,0.003256618,0.002219041,0.001705559,0.003066855,0.0009009432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02053345,"about_ca_system_score_gemma":0.02392362,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9385665,"about_ca_topic_score_gemma":0.8897483,"domain_scores_codex":[0.9913505,0.005178143,0.0003614265,0.001199013,0.001030148,0.0008808062],"domain_scores_gemma":[0.9263058,0.05398596,0.005098509,0.004589063,0.007907374,0.002113228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004236942,0.001435741,0.8162552,0.0004427401,0.002237126,0.0004297337,0.005079086,0.07510806,0.0002635235,0.03424761,0.01030696,0.04995738],"study_design_scores_gemma":[0.000826774,0.0004496287,0.4452956,0.0004874956,0.001428123,0.0003090686,0.006893182,0.5141726,0.0002049799,0.02407775,0.00557907,0.0002757454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784203,0.002293651,0.0100424,0.002388782,0.00009581808,0.0001837427,0.002609482,0.0001139388,0.003851858],"genre_scores_gemma":[0.9901114,0.001017359,0.00336977,0.0001876671,0.00004354697,0.00007077909,0.002175414,0.00006381345,0.002960149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06143349,"threshold_uncertainty_score":0.1489813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2940850762914359,"score_gpt":0.4242839251732541,"score_spread":0.1301988488818182,"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."}}