{"id":"W7128821626","doi":"10.1109/icuis67429.2025.11380545","title":"Smart Trip Planner for Personalized Tourism Itineraries","year":2025,"lang":"","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Planner; Tourism; Process (computing); Work (physics); Plan (archaeology)","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":[0.000223282,0.0005510705,0.0002186941,0.0003804455,0.0002568102,0.00054994,0.0006648686,0.0004447389,0.0160788],"category_scores_gemma":[0.0008016553,0.0002638351,0.0003875474,0.0003022043,0.0001561833,0.0007025951,0.0006992105,0.0005516691,0.004395298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002645381,"about_ca_system_score_gemma":0.0004251759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001978868,"about_ca_topic_score_gemma":0.004408597,"domain_scores_codex":[0.9999152,0.00002089286,0.000005048893,0.0000257406,0.00002404793,0.000009024872],"domain_scores_gemma":[0.9998053,0.00008158047,0.00001441183,0.00003689248,0.0000310426,0.00003085235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00114069,0.0005213478,0.007466902,0.001312521,0.0001412065,0.001252629,0.002419641,0.1147121,0.04511854,0.03500563,0.1487466,0.6421621],"study_design_scores_gemma":[0.000211842,0.0002758484,0.003878718,0.000148502,0.0001299246,0.0007006105,0.0007381479,0.6915092,0.02540965,0.02813899,0.2487116,0.0001469895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03720524,0.0003619397,0.8609878,0.0005027787,0.0002211074,0.00043825,0.004386439,0.06532962,0.03056685],"genre_scores_gemma":[0.4678285,0.0005421358,0.5006844,0.0003221606,0.00004614931,0.0006524331,0.005955205,0.00210649,0.02186252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0160788,"threshold_uncertainty_score":0.05378896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02206539330883717,"score_gpt":0.3221410795171187,"score_spread":0.3000756862082816,"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."}}