{"id":"W2056487692","doi":"10.1080/13658816.2012.682578","title":"A review of quantitative methods for movement data","year":2012,"lang":"en","type":"review","venue":"International Journal of Geographical Information Systems","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":184,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Movement (music); Computer science; Field (mathematics); Data mining; Data science; Visualization; Spatial analysis; Object (grammar); Time geography; Geovisualization; Similarity (geometry); Geography; Information retrieval; Artificial intelligence; Information visualization; Historical geography; Mathematics; Human geography; Remote sensing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.02350881,0.002062849,0.003891903,0.01366584,0.0009093999,0.003974795,0.004120263,0.002584935,0.008559386],"category_scores_gemma":[0.05218722,0.001337879,0.002370551,0.01714576,0.003398731,0.005053816,0.002087957,0.002903159,0.003875091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003536451,"about_ca_system_score_gemma":0.006326616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008517228,"about_ca_topic_score_gemma":0.01011856,"domain_scores_codex":[0.9865441,0.006343415,0.001722268,0.001473543,0.003700208,0.0002165642],"domain_scores_gemma":[0.9339541,0.05475254,0.001988832,0.002089917,0.006953869,0.0002609174],"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":[0.00004620318,0.00006629127,0.0008620903,0.02461952,0.0002588927,0.00008134268,0.0002829359,0.0008888133,0.0003810145,0.02428673,0.03395851,0.9142676],"study_design_scores_gemma":[0.00003462191,0.0001085011,0.005483813,0.02784875,0.0003872667,0.0007396252,0.0004717222,0.001738354,0.0007320429,0.06148783,0.9007741,0.000193464],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002741679,0.9376435,0.05101641,0.004257327,0.001387135,0.0002197841,0.001272843,0.0001502618,0.00377864],"genre_scores_gemma":[0.004129576,0.9288623,0.06090459,0.001215131,0.001418362,0.0007740964,0.0009410233,0.0001003393,0.001654579],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02350881,"threshold_uncertainty_score":0.1243279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.231844511457733,"score_gpt":0.5420746283246834,"score_spread":0.3102301168669505,"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."}}