{"id":"W3135843126","doi":"10.46585/pc.2020.2.1640","title":"CAPTURING OF UNEVEN DEFORMATIONS OF LIGHTENED 3D PRINTED PARTS","year":2020,"lang":"en","type":"article","venue":"Perner s Contacts","topic":"High-Velocity Impact and Material Behavior","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Necking; Deformation (meteorology); Maraging steel; Ultimate tensile strength; Fracture (geology); Materials science; Tensile testing; Stress (linguistics); Composite material; Structural engineering; Engineering","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":[0.0001742806,0.0003287303,0.0001838449,0.0008327319,0.0001255419,0.0003293605,0.00031555,0.0003418037,0.00206557],"category_scores_gemma":[0.0004979726,0.0002547605,0.0001815034,0.0004112124,0.0003195047,0.0003621904,0.0003993568,0.0003696931,0.0003167831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002025278,"about_ca_system_score_gemma":0.0001524055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002937904,"about_ca_topic_score_gemma":0.0009534559,"domain_scores_codex":[0.9997256,0.00001961225,0.00001047013,0.00005020209,0.0001653311,0.00002868942],"domain_scores_gemma":[0.9995688,0.0001301626,0.00006206178,0.0001544441,0.00005806183,0.00002651502],"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":[0.00009566289,0.000025126,0.001346761,0.00007097803,0.00001107374,0.0002046271,0.0001595576,0.006493523,0.953927,0.0002919033,0.0001379841,0.0372358],"study_design_scores_gemma":[0.00001602976,0.0003119974,0.05548364,0.0000204766,0.0000250143,0.001245221,0.0002926664,0.09183178,0.8471379,0.0005121646,0.003045964,0.00007708115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8741468,0.0001823376,0.1212421,0.00004268441,0.00003223027,0.00004515428,0.0002448086,0.0005986168,0.003465412],"genre_scores_gemma":[0.961302,0.00008862679,0.03665332,0.00001831023,0.000009291616,0.0000174227,0.0001219065,0.0000589951,0.001730036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00206557,"threshold_uncertainty_score":0.006910026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235635263714143,"score_gpt":0.2558807376806086,"score_spread":0.2235243850434672,"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."}}