{"id":"W2579692817","doi":"10.1109/ism.2016.0044","title":"E-Tourism: Mobile Dynamic Trip Planner","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Planner; TRIPS architecture; Computer science; Tourism; Recommender system; Orienteering; Algorithm design; Mobile computing; Operations research; Mathematical optimization; World Wide Web; Algorithm; Artificial intelligence; Computer network; Engineering; Operating system; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001182098,0.00007078375,0.00006515244,0.00006290479,0.00003829717,0.00009928741,0.0008128639,0.00001880523,0.000229324],"category_scores_gemma":[0.000005143057,0.00003877139,0.00002843811,0.000132321,0.00001673174,0.0007829258,0.0003194133,0.000022566,0.001176277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001413475,"about_ca_system_score_gemma":0.000007720683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006346962,"about_ca_topic_score_gemma":0.000003175658,"domain_scores_codex":[0.9993266,0.00001268061,0.0000923731,0.000243332,0.000137415,0.0001875865],"domain_scores_gemma":[0.9994048,0.00003159451,0.00002315856,0.0004799331,0.00001265544,0.00004781003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000156586,0.0000402185,0.00007617344,0.000002866761,0.00001184457,0.00003201367,0.00002541076,0.00000191899,0.0003068358,0.03704859,0.09675099,0.8657016],"study_design_scores_gemma":[0.001359986,0.0002033726,0.002124998,0.0000274079,0.000007607446,0.000009975293,0.0000299524,0.05706341,0.001246585,0.01419309,0.9232154,0.0005182585],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001923881,0.00003202057,0.9700093,0.001664743,0.0004062839,0.0001074187,0.000005352951,0.0002875078,0.02556345],"genre_scores_gemma":[0.5488926,0.0001173828,0.1050092,0.001428461,0.0001933887,0.0000809897,0.0000130911,0.00001925785,0.3442456],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8651833,"threshold_uncertainty_score":0.9996014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006716947227403578,"score_gpt":0.2266533387469146,"score_spread":0.219936391519511,"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."}}