{"id":"W6926061713","doi":"10.21227/8m8n-t819","title":"Trailer Mass Estimation Using System Model-Based and Machine Learning Approaches","year":2020,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Trailer; CarSim; Payload (computing); Track (disk drive); Articulated vehicle; Data acquisition","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006423157,0.00226989,0.001181524,0.001952026,0.0003358739,0.0007782354,0.001780389,0.001407039,0.003798383],"category_scores_gemma":[0.001819745,0.0003980411,0.001047986,0.001660227,0.0003334695,0.000929795,0.000942774,0.0007885649,0.004159308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006239848,"about_ca_system_score_gemma":0.0006177165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01915826,"about_ca_topic_score_gemma":0.02478569,"domain_scores_codex":[0.9995288,0.00006512522,0.00003364274,0.0002022013,0.00009573738,0.00007467179],"domain_scores_gemma":[0.9995554,0.0001298316,0.00005218018,0.0001296052,0.0001112092,0.00002177088],"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":[0.0005642957,0.0005015121,0.01706931,0.000646275,0.0002858697,0.000305537,0.00004363191,0.6810871,0.003780127,0.001532109,0.0886388,0.2055454],"study_design_scores_gemma":[0.00003991634,0.00007908586,0.004733443,0.00003068874,0.00003441286,0.00005590096,0.00002406406,0.9849739,0.001578194,0.001424558,0.007001219,0.00002463136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2861772,0.006113253,0.4629359,0.001123888,0.0008345612,0.0005351925,0.1992001,0.02584526,0.01723464],"genre_scores_gemma":[0.5988148,0.0009652663,0.07576827,0.0002192525,0.0001655807,0.0004595523,0.3133755,0.0003801576,0.009851628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01915826,"threshold_uncertainty_score":0.03809351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1157482001160105,"score_gpt":0.2354052332840601,"score_spread":0.1196570331680497,"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."}}