{"id":"W1595936530","doi":"10.1007/978-3-540-39646-8_22","title":"An Evidence-Based Mobility Prediction Agent Architecture","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Dempster–Shafer theory; Quality of service; Architecture; Mobility model; A priori and a posteriori; Key (lock); Wireless network; Wireless; Quality (philosophy); Artificial intelligence; Data mining; Distributed computing; Computer network; Computer security; Telecommunications","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":[0.001999531,0.0006529671,0.001220139,0.001267442,0.0007824863,0.001488012,0.004242955,0.001904975,0.004810019],"category_scores_gemma":[0.005926927,0.0006947708,0.000688823,0.0009835833,0.0006500252,0.002494859,0.002101569,0.001351486,0.001052534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009709496,"about_ca_system_score_gemma":0.001955329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01048882,"about_ca_topic_score_gemma":0.01348238,"domain_scores_codex":[0.9994239,0.0001298769,0.00006943302,0.0001497237,0.0001784594,0.00004863069],"domain_scores_gemma":[0.9982064,0.0007924204,0.0001192347,0.0001824483,0.000603346,0.00009620826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006394736,0.0004412071,0.006672241,0.0002388837,0.000367216,0.0003546809,0.0002252262,0.5076412,0.004070275,0.03250651,0.00645284,0.4403902],"study_design_scores_gemma":[0.00002860882,0.00004693548,0.0002685273,0.00001542902,0.00008046975,0.00005026465,0.00001393404,0.9877139,0.001075969,0.009500907,0.001193988,0.00001107961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01945238,0.000376829,0.9739594,0.0009974012,0.00008047852,0.0002070177,0.0003087789,0.001818367,0.002799349],"genre_scores_gemma":[0.4228432,0.0004474821,0.5689424,0.0002777048,0.00008193815,0.0003961528,0.0006570246,0.00008743742,0.006266607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01048882,"threshold_uncertainty_score":0.02085555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0341941035728734,"score_gpt":0.2973947169804392,"score_spread":0.2632006134075658,"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."}}