{"id":"W4232918740","doi":"10.32920/14638491.v1","title":"Road Surface Monitoring Using Smartphone Sensors: A Review","year":2021,"lang":"en","type":"review","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Road surface; Anomaly detection; Key (lock); Anomaly (physics); Computer science; Smartphone application; Plan (archaeology); Real-time computing; Computer security; Transport engineering; Remote sensing; Engineering; Artificial intelligence; Geography; Multimedia; Civil engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002341587,0.0007386156,0.002569466,0.00009117676,0.00007680397,0.00008098013,0.0002829838,0.0003447653,0.0001812077],"category_scores_gemma":[0.00005167889,0.0006222037,0.0006734786,0.0006066713,0.00001949951,0.0001313235,0.0001116889,0.0007514252,0.0001129362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004187205,"about_ca_system_score_gemma":0.0001293021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002661479,"about_ca_topic_score_gemma":5.814698e-7,"domain_scores_codex":[0.9977451,0.00008338878,0.0008345779,0.0004322714,0.0002760645,0.0006285952],"domain_scores_gemma":[0.9989001,0.00005832841,0.0001301822,0.0006762426,0.0001014895,0.0001336974],"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":[1.173756e-7,0.000003424937,0.000002524587,0.1091941,0.0002447371,0.0001001856,0.00001496521,0.0009261139,0.00001034969,0.000006342606,0.001835022,0.8876621],"study_design_scores_gemma":[0.00003548636,0.000002680655,4.558696e-7,0.2135521,0.0005744515,0.0001788972,0.00001362779,0.00008995337,0.00004408916,8.421131e-7,0.7849654,0.0005420371],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001896106,0.9924226,0.0002790837,0.000002042006,0.004106402,0.000459765,0.00001085996,0.0004348618,0.002265435],"genre_scores_gemma":[0.000002713604,0.9917288,0.005956383,0.000009955069,0.00147392,0.0000211886,0.00002728918,0.0002015414,0.000578189],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8871201,"threshold_uncertainty_score":0.9996229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04945535995273322,"score_gpt":0.3250608205284554,"score_spread":0.2756054605757222,"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."}}