{"id":"W329253758","doi":"10.17975/sfj-2015-013","title":"Big Data in the City","year":2015,"lang":"en","type":"article","venue":"STEM Fellowship Journal","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005499645,0.0006094008,0.0008136588,0.005302445,0.003436662,0.01203294,0.001264118,0.002909454,0.009626358],"category_scores_gemma":[0.02362484,0.0007408158,0.001007408,0.01614484,0.004620575,0.01402889,0.007424471,0.005678106,0.002208125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004557734,"about_ca_system_score_gemma":0.005773375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02191127,"about_ca_topic_score_gemma":0.02259582,"domain_scores_codex":[0.9955889,0.001740701,0.0002455279,0.0005975054,0.001477733,0.000349563],"domain_scores_gemma":[0.9861336,0.00626957,0.001027354,0.002483527,0.002390388,0.001695562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00009508072,0.00004235355,0.02848187,0.0008144479,0.0002874108,0.0004789022,0.004483014,0.005619087,0.0002859465,0.4790576,0.3601124,0.1202418],"study_design_scores_gemma":[0.00001838064,0.00001733871,0.01461005,0.001028558,0.00004859706,0.0001981674,0.005346434,0.004360876,0.000195635,0.3624487,0.6116436,0.00008362821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05263248,0.07276533,0.07754943,0.5696917,0.01302492,0.000305468,0.03792366,0.002034987,0.1740722],"genre_scores_gemma":[0.7003397,0.08280085,0.07433748,0.06539794,0.01145177,0.0008052733,0.03005289,0.001269752,0.03354434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02191127,"threshold_uncertainty_score":0.04356748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3795036483103332,"score_gpt":0.3888698296365517,"score_spread":0.009366181326218526,"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."}}