{"id":"W4403013138","doi":"10.1016/j.precisioneng.2024.09.022","title":"Rethinking wire electrical discharge machining: A case for engineering thick wires to enhance performance","year":2024,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced Machining and Optimization Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Alexander von Humboldt-Stiftung","keywords":"Electrical discharge machining; Machining; Materials science; Mechanical engineering; Engineering; Manufacturing engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002506066,0.000582471,0.0004873152,0.0004795545,0.0004532153,0.001958924,0.001059377,0.001490141,0.001337428],"category_scores_gemma":[0.003568813,0.0003221185,0.0003559557,0.0004498473,0.001274257,0.003617737,0.001195815,0.001942275,0.0005341513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006498453,"about_ca_system_score_gemma":0.0005627107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003082605,"about_ca_topic_score_gemma":0.0006823341,"domain_scores_codex":[0.9991874,0.0001574454,0.00003911926,0.0001180152,0.0003940951,0.0001039617],"domain_scores_gemma":[0.9985775,0.0006817659,0.0001298013,0.0002768955,0.0002603341,0.00007382748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003494451,0.0003158383,0.002834629,0.001676647,0.00005783332,0.001384705,0.001005105,0.06251185,0.4594183,0.1450172,0.003229924,0.3221986],"study_design_scores_gemma":[0.0001116571,0.002950674,0.004707606,0.000864077,0.0001270422,0.002352754,0.001742788,0.1449481,0.4553671,0.141166,0.2454355,0.0002266701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4046293,0.03588003,0.4904188,0.01342585,0.0009769708,0.0001656935,0.0001121679,0.0009760431,0.05341515],"genre_scores_gemma":[0.7126977,0.01560691,0.2619272,0.0007285158,0.0001431497,0.00007404087,0.00007401029,0.0003755052,0.00837288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002506066,"threshold_uncertainty_score":0.01325351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00922177401250044,"score_gpt":0.2649036097987458,"score_spread":0.2556818357862454,"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."}}