{"id":"W2801075639","doi":"10.1139/tcsme-2013-0069","title":"SUM OF SINUSOIDAL PLUS NOISE MODEL TO EXTRACT COMPONENT ERROR FROM A DOUBLE BALLBAR MEASUREMENT ERROR MAP","year":2013,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noise (video); Algorithm; Component (thermodynamics); Mathematics; Path (computing); Round-off error; Computer science; Artificial intelligence; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002165142,0.0002169345,0.0003229929,0.00007794087,0.0000963422,0.00001078459,0.0003375092,0.0001860551,0.00004615612],"category_scores_gemma":[0.00001306018,0.0002068012,0.0004940028,0.0001593982,0.00002625189,0.0001228299,0.000008106349,0.0002596161,0.000002533361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008039571,"about_ca_system_score_gemma":0.0001402727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007517169,"about_ca_topic_score_gemma":0.01543546,"domain_scores_codex":[0.9987416,0.000005447311,0.0003607289,0.0001853214,0.0002948591,0.0004120899],"domain_scores_gemma":[0.9991271,0.00002975559,0.00004060597,0.0003422702,0.0001570118,0.0003032773],"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":[0.00001229089,0.00001945726,0.000001031405,0.0000865807,0.0001600658,7.156204e-8,0.0001539311,0.6963185,0.3023149,0.0001794265,0.0004666792,0.0002870026],"study_design_scores_gemma":[0.0007201282,0.00005247508,0.00003451205,0.0001097865,0.0001202278,6.289073e-7,0.00006938813,0.8063121,0.1909475,0.0002902777,0.001099773,0.0002432033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03325306,0.0001559346,0.9643652,0.0004684598,0.0003404809,0.001045074,0.0001689705,0.0001705913,0.00003227028],"genre_scores_gemma":[0.9099876,0.000004539364,0.08954798,0.0000596369,0.00002630967,0.0002783891,0.000005792501,0.00005219645,0.00003756174],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8767346,"threshold_uncertainty_score":0.9990919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03878944243173547,"score_gpt":0.2319915465758114,"score_spread":0.1932021041440759,"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."}}