{"id":"W4400235760","doi":"10.11159/ffhmt24.018","title":"Metal Powder Handling In Additive Manufacturing Application","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Process engineering; Manufacturing engineering; Metallurgy; Materials science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008252626,0.0009917105,0.0008121898,0.001854418,0.001018758,0.002522107,0.00217457,0.00180803,0.02585927],"category_scores_gemma":[0.001537957,0.0004137341,0.0006543812,0.00340518,0.0005842157,0.002055024,0.001568303,0.0009992103,0.02416205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009370775,"about_ca_system_score_gemma":0.0008574356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007561989,"about_ca_topic_score_gemma":0.000664283,"domain_scores_codex":[0.9975687,0.0001876863,0.0001853448,0.0004446605,0.001457524,0.0001561385],"domain_scores_gemma":[0.9990938,0.000142276,0.0001275366,0.0001446048,0.0004395758,0.00005225416],"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":[0.0002194286,0.0002108014,0.001896558,0.004037048,0.00003629002,0.0009881975,0.0003231607,0.001882419,0.1062441,0.0227109,0.04805905,0.8133919],"study_design_scores_gemma":[0.00001546076,0.0002564792,0.001441875,0.0003752162,0.00004894207,0.002136962,0.0001261232,0.002251225,0.07254521,0.004597923,0.9161643,0.00004036972],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04335661,0.1320075,0.3200828,0.003371403,0.004710598,0.001366024,0.002478461,0.009116611,0.48351],"genre_scores_gemma":[0.3928386,0.08784433,0.2740795,0.006095191,0.003625987,0.0007877069,0.006338913,0.002006476,0.2263833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02585927,"threshold_uncertainty_score":0.08650786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515223245283596,"score_gpt":0.2244266562761334,"score_spread":0.2092744238232975,"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."}}