{"id":"W2925239908","doi":"10.5441/002/edbt.2019.13","title":"GroupTravel: Customizing Travel Packages for Groups","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Group cohesiveness; Personalization; Point of interest; Computer science; Group (periodic table); Information retrieval; World Wide Web; Data mining; Artificial intelligence; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0136537,0.0003464518,0.0005562322,0.0002709295,0.001216522,0.000674416,0.001557218,0.0005221004,0.0003896803],"category_scores_gemma":[0.003405354,0.0003934645,0.000548773,0.0004385578,0.000539644,0.0001756827,0.0004300122,0.0006300383,0.00009223937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003177645,"about_ca_system_score_gemma":0.0008858579,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01856888,"about_ca_topic_score_gemma":0.0547126,"domain_scores_codex":[0.9910678,0.006131527,0.0006335584,0.0009748327,0.0006356291,0.0005567053],"domain_scores_gemma":[0.9911892,0.003732069,0.000569012,0.00179389,0.00246874,0.0002470748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003692431,0.001128395,0.004908732,0.0008031416,0.000391283,0.000002303327,0.1633411,0.0006406452,0.001021599,0.7015175,0.00382189,0.1223865],"study_design_scores_gemma":[0.007088558,0.000006039721,0.05516699,0.01197844,0.002241672,0.000005819595,0.05428392,0.1929675,0.04212869,0.2467921,0.3792357,0.008104653],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07257929,0.001098241,0.7938961,0.02276982,0.0006424505,0.002035446,0.0002230677,0.0004099512,0.1063456],"genre_scores_gemma":[0.968762,0.0005507591,0.00918304,0.0001747028,0.0001294547,0.0002160015,0.0007273715,0.00005356719,0.02020307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8961827,"threshold_uncertainty_score":0.9998517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02225745457831924,"score_gpt":0.2706075190135111,"score_spread":0.2483500644351919,"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."}}