{"id":"W7082250492","doi":"10.5281/zenodo.17159059","title":"Medical tourism","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical tourism; Tourism; Phenomenon; Legislation; Health care; Developed country; Competition (biology); Quality (philosophy)","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":[0.0006467449,0.0004583603,0.0004013969,0.001677232,0.001989828,0.00442489,0.0008131829,0.001615717,0.2462601],"category_scores_gemma":[0.002928356,0.0001423675,0.0004912782,0.002070771,0.0008026957,0.001730112,0.003186824,0.001368744,0.08975548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001362261,"about_ca_system_score_gemma":0.003331952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002022218,"about_ca_topic_score_gemma":0.004471465,"domain_scores_codex":[0.9990535,0.0002498604,0.00008177351,0.0001044938,0.0003275376,0.0001827145],"domain_scores_gemma":[0.9986445,0.0001898694,0.0001322578,0.00009198399,0.0003628017,0.0005785095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007328929,0.00009160316,0.001930223,0.001247999,0.00001575219,0.0004300047,0.0009935981,0.0001168364,0.0002791393,0.03018712,0.7446106,0.2200239],"study_design_scores_gemma":[0.000005396206,0.00003574706,0.002657298,0.0003720823,0.000002558654,0.0004181547,0.0007003011,0.00002985096,0.0000407422,0.001377678,0.9943529,0.000007118646],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008398076,0.01856689,0.001406273,0.02263273,0.00757381,0.0003338982,0.005521127,0.0004815421,0.9350857],"genre_scores_gemma":[0.06469479,0.0343307,0.003302658,0.01246825,0.003920575,0.0003222929,0.007476948,0.0002610071,0.8732228],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2462601,"threshold_uncertainty_score":0.8238221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01888152835385615,"score_gpt":0.23791019998295,"score_spread":0.2190286716290938,"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."}}