{"id":"W3184463446","doi":"10.1016/j.jmapro.2021.07.024","title":"Determination of optimum vibro-compaction time using sound analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Aluminerie Alouette (Canada); Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Chicoutimi","keywords":"Compaction; Anode; Materials science; Fabrication; Vibration; Composite material; Metallurgy; Acoustics; Electrode","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002027854,0.0001299354,0.0003352725,0.0004238948,0.00004000076,0.00004997061,0.0001319769,0.0000615004,0.00005127482],"category_scores_gemma":[0.0001883391,0.0001278232,0.0001186141,0.0004286807,0.00002553027,0.0004608725,0.00002281555,0.0001731025,0.000001066043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001293715,"about_ca_system_score_gemma":0.00007015125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004066451,"about_ca_topic_score_gemma":0.000003156281,"domain_scores_codex":[0.9990633,0.00002659101,0.0004359341,0.00009283185,0.0002505511,0.0001307797],"domain_scores_gemma":[0.9989377,0.0001375694,0.0003542517,0.0001236722,0.0004002397,0.00004652596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001159291,0.0002792205,0.01293101,0.004850478,0.0025369,0.000276868,0.001395219,0.5233166,0.4456996,0.0000303749,0.0001045816,0.008463229],"study_design_scores_gemma":[0.0001254252,0.00003887641,0.004457984,0.0001776916,0.0004366518,0.0002539547,0.00004071214,0.002975817,0.9813207,0.0100242,0.00001073008,0.0001372728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8254682,0.0002078927,0.1737334,0.000006916926,0.0000714839,0.00002788545,0.000002166926,0.00007887265,0.0004030797],"genre_scores_gemma":[0.7088916,0.000027021,0.2910001,0.000002309893,0.00005597672,4.088447e-7,0.000001361993,0.000016616,0.000004547905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.535621,"threshold_uncertainty_score":0.5212477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019334815157348,"score_gpt":0.2688468530830669,"score_spread":0.2486535049314935,"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."}}