{"id":"W2429567195","doi":"10.1145/2939953.2939955","title":"Analyzing the usage patterns of electric bicycles","year":2016,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Cisco Systems","keywords":"Computer science","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":[0.0002539636,0.0001391822,0.000212985,0.001255398,0.0002003748,0.0003673431,0.0002239822,0.0002099467,0.0009641346],"category_scores_gemma":[0.001773715,0.00009857379,0.0001079575,0.001889338,0.0002001306,0.000331587,0.0003168033,0.0001249996,0.0003354464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002697527,"about_ca_system_score_gemma":0.0002606115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04885747,"about_ca_topic_score_gemma":0.1446033,"domain_scores_codex":[0.9997227,0.00005572817,0.00002172957,0.00007269938,0.00007312857,0.00005405672],"domain_scores_gemma":[0.9990684,0.0002679833,0.0001954449,0.00007450973,0.0003143527,0.00007941147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002282142,0.00009987727,0.954644,0.0001033329,0.00007200492,0.0001877516,0.001919711,0.001910711,0.006389494,0.0002020041,0.001702445,0.03254026],"study_design_scores_gemma":[0.000004866628,0.00005376019,0.9896147,0.00001773863,0.00001547511,0.0001289882,0.002046502,0.005457602,0.0007628017,0.00007241147,0.001812086,0.0000133241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980575,0.00003740178,0.0002777963,0.0000230942,0.000001023324,0.000006695284,0.00107157,0.000008660432,0.0005160946],"genre_scores_gemma":[0.9969031,0.00005305849,0.0004302462,0.00001039842,0.00000262822,0.00001396981,0.002011199,0.000004869555,0.0005705411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04885747,"threshold_uncertainty_score":0.09714615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01806766106409362,"score_gpt":0.2912521339913269,"score_spread":0.2731844729272333,"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."}}