{"id":"W4239881089","doi":"10.32920/ryerson.14649390.v1","title":"Compaction density variation in powder metallurgy components","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Powder Metallurgy Techniques and Materials","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Compaction; Powder metallurgy; Relative density; Materials science; Sintering; Finite element method; Density estimation; Composite material; Metallurgy; Mathematics; Engineering; Structural engineering; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002858524,0.0002746113,0.0005272141,0.0001882519,0.00001884613,0.0001295665,0.0001496155,0.0003602001,0.0006924844],"category_scores_gemma":[0.00001323696,0.0002947106,0.000114835,0.00009187478,0.00001064539,0.0001285231,0.0002392148,0.00035917,0.00002552343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002141735,"about_ca_system_score_gemma":0.00002439706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001289769,"about_ca_topic_score_gemma":0.0003016312,"domain_scores_codex":[0.9987822,0.00008626172,0.0004226106,0.0003021197,0.0001787603,0.0002280414],"domain_scores_gemma":[0.9994133,0.00001914255,0.00006571777,0.0003940129,0.0000494821,0.00005840152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002444788,0.00025662,0.0003116084,0.0008496012,0.0005521476,0.0001075856,0.0006510515,0.09314995,0.9000625,0.00183009,0.0009933645,0.001211005],"study_design_scores_gemma":[0.001425282,0.00003907448,0.3618197,0.000931067,0.0003487585,0.00008074576,0.0001218108,0.3090644,0.3066656,0.009285946,0.007248597,0.002969017],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8847578,0.0001145838,0.1064993,0.00004246378,0.002045411,0.0003038475,0.000005275145,0.0008520289,0.005379275],"genre_scores_gemma":[0.9926326,0.0002051889,0.00659665,0.00005181823,0.00007012666,0.00004385209,0.0002433562,0.00004280495,0.0001136586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5933969,"threshold_uncertainty_score":0.9999505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02536360657582377,"score_gpt":0.2400669422818443,"score_spread":0.2147033357060206,"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."}}