{"id":"W3156336256","doi":"10.25518/esaform21.455","title":"Punching with a slant angle - cutting surface quality","year":2021,"lang":"en","type":"article","venue":"ESAFORM 2021","topic":"Mechanical Behavior of Composites","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Forming Technologies (Canada)","funders":"","keywords":"Punching; Sheet metal; Enhanced Data Rates for GSM Evolution; Surface (topology); Quality (philosophy); Structural engineering; Mechanical engineering; Geometry; Engineering; Computer science; Mathematics; Artificial intelligence; Physics","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":[0.0007655852,0.0004382068,0.0002227451,0.0007601905,0.00025861,0.0006535844,0.0002860405,0.0005923897,0.003338233],"category_scores_gemma":[0.00198536,0.0002877596,0.0002870566,0.0008865854,0.0004443638,0.0005128344,0.000344376,0.0005404225,0.0007446929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320609,"about_ca_system_score_gemma":0.000170893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006899287,"about_ca_topic_score_gemma":0.001201143,"domain_scores_codex":[0.9987514,0.00007101901,0.00006908904,0.0001843325,0.0008352997,0.0000887946],"domain_scores_gemma":[0.9973357,0.000872074,0.0005137473,0.0003493495,0.0008620974,0.00006699128],"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":[0.0002432195,0.00008191029,0.01610717,0.0002028399,0.00002235971,0.0001552183,0.0002822176,0.004451748,0.9255375,0.0003128561,0.0002876173,0.05231538],"study_design_scores_gemma":[0.00001163035,0.001104833,0.1501909,0.0000372186,0.00004616517,0.0006164673,0.0004705949,0.01297684,0.8303791,0.0004119635,0.003695003,0.00005940316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703591,0.001404748,0.02196937,0.00003433265,0.00004278238,0.00006522315,0.0004122832,0.000295632,0.005416488],"genre_scores_gemma":[0.9952111,0.0001755105,0.003328858,0.00001382202,0.000003626812,0.00001302992,0.0002104135,0.00003580303,0.001007934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003338233,"threshold_uncertainty_score":0.01116753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669870626280593,"score_gpt":0.2497049098357417,"score_spread":0.2330062035729357,"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."}}