{"id":"W35714046","doi":"10.1111/gcb.16304","title":"Signal processing: key element in designing an accurate machining forces measuring device","year":2009,"lang":"en","type":"article","venue":"International Conference on Signal Processing","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Machining; Key (lock); SIGNAL (programming language); Computer science; Signal processing; Process (computing); Mechanical engineering; Engineering drawing; Engineering; Control engineering; Computer hardware; Digital signal processing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001500364,0.001085303,0.0005741672,0.001147321,0.0005014307,0.001662567,0.001345791,0.001320626,0.006125785],"category_scores_gemma":[0.003486819,0.0005763802,0.0004285433,0.0008949242,0.0005206088,0.002187463,0.0006821365,0.001017545,0.004984762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003925496,"about_ca_system_score_gemma":0.000760617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008882068,"about_ca_topic_score_gemma":0.0007358435,"domain_scores_codex":[0.9989545,0.0001300456,0.00009266737,0.0002457511,0.0004966318,0.00008045531],"domain_scores_gemma":[0.99834,0.000553232,0.0001419533,0.0001312003,0.0007873885,0.00004622525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002665464,0.0001417979,0.005065351,0.001157752,0.00007390643,0.0003585865,0.0003046455,0.0182149,0.2428156,0.01161787,0.01050218,0.7094809],"study_design_scores_gemma":[0.0001121207,0.001309193,0.01069921,0.0005370209,0.0002633943,0.001626963,0.0005005172,0.5209976,0.2814287,0.01813147,0.1641389,0.000254763],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006771958,0.000742333,0.9856657,0.0006376246,0.0002094222,0.0002436642,0.00017431,0.001433616,0.004121416],"genre_scores_gemma":[0.1626051,0.001430752,0.8284901,0.0007107641,0.0004153399,0.0005539228,0.0005314082,0.0002531883,0.005009476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006125785,"threshold_uncertainty_score":0.02049279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09688666087113913,"score_gpt":0.3325832467574097,"score_spread":0.2356965858862706,"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."}}