{"id":"W2965700358","doi":"10.18280/isi.240206","title":"Spatial Data Mining and Big Data Analysis of Tourist Travel Behavior","year":2019,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tourism; Big data; Data science; Data mining; Travel behavior; Computer science; Geography; Transport engineering; Engineering; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000825015,0.0002282893,0.0004777782,0.001414389,0.0002188278,0.0004264845,0.001026458,0.0002592017,0.0002803431],"category_scores_gemma":[0.0003693125,0.0002508958,0.00005094034,0.002357468,0.0003871012,0.01004851,0.001395909,0.0001731848,0.00008454736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004875968,"about_ca_system_score_gemma":0.00006071986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005180549,"about_ca_topic_score_gemma":0.001586574,"domain_scores_codex":[0.9981314,0.00001671047,0.000984852,0.0003025318,0.0002623305,0.0003021969],"domain_scores_gemma":[0.9969065,0.00007255974,0.0009264451,0.001684568,0.000394393,0.00001560271],"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":[0.00001980823,0.00008808247,0.4231978,0.001138971,0.000721171,0.00000257389,0.0006301711,0.00002230723,0.00006996198,0.005917359,0.004479006,0.5637128],"study_design_scores_gemma":[0.001232647,0.0000579737,0.6955944,0.0006803692,0.006647156,0.00001473489,0.0103342,0.2203941,0.00007106276,0.0004156953,0.06380316,0.0007544099],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688418,0.0009421735,0.01554198,0.00129485,0.001603468,0.0005979164,0.001722809,0.00009842117,0.009356581],"genre_scores_gemma":[0.9836074,0.00009063084,0.001595125,0.0003372408,0.0002507037,0.0000123788,0.01382042,0.00001514946,0.0002710133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5629584,"threshold_uncertainty_score":0.9999943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05170301978996044,"score_gpt":0.2606678335529969,"score_spread":0.2089648137630364,"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."}}