{"id":"W3007902165","doi":"10.1145/3362063","title":"Differentiating Population Spatial Behavior Using Representative Features of Geospatial Mobility (ReFGeM)","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Spatial Algorithms and Systems","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Saskatchewan","funders":"Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Geospatial analysis; Set (abstract data type); Global Positioning System; Feature (linguistics); Scope (computer science); Scale (ratio); Population; Spatial analysis","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002038981,0.0005919495,0.0006353433,0.004097327,0.0003836182,0.00106333,0.0006454822,0.0005671195,0.001108314],"category_scores_gemma":[0.009000039,0.0001722917,0.0009365862,0.003412987,0.0006003621,0.001353233,0.001375898,0.0004622129,0.0003611513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006285797,"about_ca_system_score_gemma":0.0006047088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006053231,"about_ca_topic_score_gemma":0.01011538,"domain_scores_codex":[0.9987539,0.0004127695,0.000152763,0.000337143,0.0002260604,0.0001173725],"domain_scores_gemma":[0.9970126,0.001023178,0.000638202,0.0007966323,0.0004318159,0.0000975683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003886354,0.0003152796,0.566169,0.0005246936,0.0004706559,0.000354637,0.001182615,0.05921788,0.006832418,0.01669148,0.01116249,0.3366902],"study_design_scores_gemma":[0.00005064968,0.0003249251,0.4835655,0.0001289134,0.0001607749,0.0007231107,0.001581181,0.4563365,0.00479318,0.03605453,0.01614203,0.0001386747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6092751,0.0003320337,0.3629793,0.0004426067,0.0000717477,0.0004061835,0.01938435,0.002385459,0.004723236],"genre_scores_gemma":[0.9230992,0.00005659131,0.06893077,0.00002988892,0.00002186947,0.0002278556,0.007323879,0.00004168959,0.000268242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006053231,"threshold_uncertainty_score":0.01203603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05694619294302973,"score_gpt":0.3329686332956746,"score_spread":0.2760224403526449,"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."}}