{"id":"W2746197122","doi":"10.2196/mhealth.7167","title":"Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study","year":2017,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Physical Activity and Health","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dublin City University; European Commission","keywords":"Movement (music); Geocoding; Computer science; Measure (data warehouse); Smartphone app; Human–computer interaction; Field (mathematics); Cartography; Geography; 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":[0.0115409,0.001053085,0.0005463455,0.0008025297,0.0006743601,0.0005620999,0.001179905,0.001092397,0.001379719],"category_scores_gemma":[0.01409919,0.0003234189,0.0009300254,0.0004845169,0.001357097,0.0007273871,0.001177356,0.0007183911,0.0009293234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004423194,"about_ca_system_score_gemma":0.001139601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003903323,"about_ca_topic_score_gemma":0.006710017,"domain_scores_codex":[0.9947627,0.002516708,0.0003508661,0.000941837,0.001199715,0.0002281769],"domain_scores_gemma":[0.9893148,0.004145603,0.0006661451,0.001522117,0.004018567,0.0003328891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004323355,0.02233762,0.6940123,0.001705561,0.0007786311,0.0009771034,0.01313791,0.008005915,0.04521339,0.001792768,0.005529212,0.2021862],"study_design_scores_gemma":[0.0009058059,0.02617615,0.915248,0.0004404046,0.0004610878,0.001093077,0.004261536,0.02407411,0.01576162,0.0008393317,0.01062435,0.0001144043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982182,0.0000960074,0.012774,0.00007858346,0.00003904965,0.002625838,0.0006147521,0.00009303829,0.001496835],"genre_scores_gemma":[0.955193,0.0002259203,0.0354351,0.0002164489,0.00005916679,0.004829772,0.002450435,0.00004167853,0.001548358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0115409,"threshold_uncertainty_score":0.06103486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2780555242124291,"score_gpt":0.4946714882083102,"score_spread":0.2166159639958811,"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."}}