{"id":"W2229323108","doi":"10.1177/0263775815595814","title":"Spatial big data and anxieties of control","year":2015,"lang":"en","type":"article","venue":"Environment and Planning D Society and Space","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Big data; Feeling; Context (archaeology); Transparency (behavior); Data collection; Control (management); Psychology; Anxiety; Sociology; Data science; Internet privacy; Social psychology; Computer science; Social science; Geography; Computer security; Data mining","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008485414,0.00006098726,0.0001234465,0.00001003656,0.0002714783,0.00003391151,0.0000680548,0.00006633153,0.00001764378],"category_scores_gemma":[0.00005352216,0.00005752077,0.00001944259,0.00002781256,0.0005135751,0.00007833524,0.00005211821,0.00006627728,9.295088e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001093498,"about_ca_system_score_gemma":0.00002909224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002312737,"about_ca_topic_score_gemma":0.0002805128,"domain_scores_codex":[0.9993892,0.00008340312,0.00008546576,0.0001720241,0.0001665076,0.0001033655],"domain_scores_gemma":[0.9995964,0.0001232521,0.00004917371,0.0001230707,0.0000076537,0.0001004318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003536987,0.00005343685,0.8210926,0.00003875099,0.0001159379,0.00000108489,0.1543196,0.0002371026,0.00007887084,0.0005779103,0.004050883,0.01939849],"study_design_scores_gemma":[0.003176196,0.0002896941,0.1880926,0.00009845755,0.0004791004,0.000001427903,0.3233116,0.03184999,0.00005975915,0.002544302,0.4493901,0.000706821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824699,0.00440133,0.009714664,0.0024637,0.00005756381,0.0001154888,0.00004047112,0.00001385242,0.000723033],"genre_scores_gemma":[0.9978117,0.00128339,0.0001958286,0.00008750567,0.0001556443,0.000001620903,0.00002013171,0.000002558041,0.0004415735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.633,"threshold_uncertainty_score":0.3496182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05163223426918218,"score_gpt":0.2689874449647928,"score_spread":0.2173552106956106,"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."}}