{"id":"W3004274762","doi":"10.1139/cjce-2019-0681","title":"AI-based cloud computing application for smart earthmoving operations","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Cloud computing; Truck; Dashboard; Field (mathematics); Engineering; Computer science; Real-time computing; Database; Automotive engineering; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002761345,0.0005261154,0.0004294915,0.0004510562,0.0004161141,0.0009545466,0.001113589,0.0004531725,0.005187596],"category_scores_gemma":[0.0007549486,0.0001605881,0.0004885545,0.0007291318,0.000178544,0.0008867029,0.0005445285,0.0005370759,0.001247846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008058628,"about_ca_system_score_gemma":0.0008824146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01058864,"about_ca_topic_score_gemma":0.0091025,"domain_scores_codex":[0.9998022,0.00002378968,0.00001608671,0.0000436359,0.00008617098,0.00002818968],"domain_scores_gemma":[0.9997292,0.00005728731,0.00002536665,0.00004437214,0.0001148266,0.00002899804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004555864,0.0003613928,0.007256346,0.0004024141,0.0001118912,0.0006709974,0.000158471,0.6287981,0.01911434,0.02723951,0.03165898,0.2837721],"study_design_scores_gemma":[0.0000148182,0.00002386909,0.0008333322,0.00001226404,0.00001186081,0.00003941756,0.0000221013,0.9839795,0.002609716,0.003144996,0.009298041,0.00001008617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05902143,0.0008712855,0.8742876,0.001254484,0.0005431202,0.0006897907,0.002120866,0.01476551,0.04644585],"genre_scores_gemma":[0.7740926,0.001031354,0.2091689,0.0003581402,0.0001117464,0.0004512763,0.001734654,0.0003382212,0.01271318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01058864,"threshold_uncertainty_score":0.02105403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007765650071494714,"score_gpt":0.1874277035324239,"score_spread":0.1796620534609292,"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."}}