{"id":"W7118635703","doi":"10.18280/ijsdp.201102","title":"Comparative Bibliometric Analysis of Smart Tourism Destination Research in China and Abroad","year":2025,"lang":"","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; Tourism; Tourism geography; Smart city; Bibliometrics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002601347,0.0003101746,0.000946369,0.0993119,0.001681001,0.004116701,0.0006371639,0.0004670642,0.006844588],"category_scores_gemma":[0.01194339,0.0001325931,0.0007943953,0.1351094,0.0008004939,0.002306947,0.001745023,0.0003428882,0.0009328489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002980781,"about_ca_system_score_gemma":0.005177013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03013043,"about_ca_topic_score_gemma":0.04484043,"domain_scores_codex":[0.9962456,0.0005998281,0.0007061153,0.0003416763,0.001757147,0.0003495826],"domain_scores_gemma":[0.9809863,0.007067291,0.003439233,0.000760577,0.006636909,0.001109633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002125466,0.0001445972,0.8534046,0.003410959,0.0006203675,0.0006216209,0.006402176,0.0005352427,0.001205074,0.006328357,0.01266275,0.1144516],"study_design_scores_gemma":[0.000008727913,0.00003866856,0.9700606,0.0003501445,0.0003297782,0.0003391936,0.00767369,0.0007381861,0.0004140064,0.0004476649,0.01957183,0.00002755848],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9072139,0.02002965,0.0006437473,0.001228923,0.0001562714,0.00009544849,0.01991365,0.0001455474,0.05057285],"genre_scores_gemma":[0.9810508,0.006163845,0.0004914824,0.00007708863,0.0001587496,0.00005339106,0.0083932,0.00002109654,0.003590352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9006881,"threshold_uncertainty_score":0.05991006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04855714298726353,"score_gpt":0.4091979190456494,"score_spread":0.3606407760583858,"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."}}