{"id":"W385412081","doi":"","title":"Identification of Road Irregularities via Vehicle Accelerations","year":2010,"lang":"en","type":"article","venue":"Research Portal (Queen's University Belfast)","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Accelerometer; Range (aeronautics); Computer science; Acceleration; Entropy (arrow of time); Iterative method; Principle of maximum entropy; Algorithm; Simulation; Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001654804,0.0003625531,0.0002920531,0.00112246,0.0001152648,0.0003601453,0.0002616462,0.0002695457,0.0006529948],"category_scores_gemma":[0.0007311995,0.0001577097,0.0001834664,0.0005282817,0.0001489808,0.0003174113,0.0002651529,0.0002373223,0.0003622555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001808706,"about_ca_system_score_gemma":0.0002524689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004233063,"about_ca_topic_score_gemma":0.004862818,"domain_scores_codex":[0.9998525,0.00001777675,0.000005086339,0.00003476578,0.00007088148,0.00001888298],"domain_scores_gemma":[0.9997742,0.00006066619,0.0000566502,0.00003051701,0.00006194786,0.00001610511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003565363,0.0001669718,0.1193607,0.0001577472,0.00009405367,0.0002565836,0.0002716106,0.4950197,0.08840016,0.00127345,0.0009171092,0.2937253],"study_design_scores_gemma":[0.000006925805,0.0001025993,0.0919351,0.0000117745,0.0000153536,0.0001058984,0.00008156285,0.8921253,0.01422033,0.0004543134,0.000918936,0.00002191194],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.748919,0.0001013651,0.2465852,0.00003654746,0.00001657905,0.00006160286,0.0004641144,0.0008302598,0.002985301],"genre_scores_gemma":[0.979567,0.00004610531,0.01945073,0.000002775517,0.000003528891,0.00001269151,0.000286896,0.00001959055,0.0006107097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004233063,"threshold_uncertainty_score":0.008416831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153906250036676,"score_gpt":0.2520167665195168,"score_spread":0.2404777040191501,"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."}}