{"id":"W2902692830","doi":"10.3390/ma11122386","title":"A Comprehensive Approach to Powder Feedstock Characterization for Powder Bed Fusion Additive Manufacturing: A Case Study on AlSi7Mg","year":2018,"lang":"en","type":"article","venue":"Materials","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Raw material; Cohesion (chemistry); Particle size; Particle-size distribution; Composite material; Rheology; Metal powder; Particle (ecology); Porosity; Moisture; Bulk density; Powder metallurgy; Sintering; Metallurgy; Chemical engineering; Metal; Environmental science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001417906,0.0003519806,0.0003972053,0.0002383474,0.0002362285,0.0001365406,0.0002041737,0.0001452369,0.0001151478],"category_scores_gemma":[0.00004356349,0.0003190406,0.0000505886,0.00008937799,0.00005421981,0.00009361103,0.0001650487,0.00009662965,0.0001432422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000805178,"about_ca_system_score_gemma":0.000006379415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003460671,"about_ca_topic_score_gemma":0.000002697416,"domain_scores_codex":[0.9985974,0.00006159647,0.0003314827,0.0004531407,0.0001534206,0.0004029317],"domain_scores_gemma":[0.9992344,0.00008607208,0.00008256771,0.0004205044,0.0001039074,0.00007259238],"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":[0.0004958026,0.0006638398,0.00003468571,0.0003227946,0.0004240799,0.0001974871,0.009122364,0.0001162671,0.9488136,0.0002223314,0.004318031,0.03526871],"study_design_scores_gemma":[0.0006473243,0.0006083769,0.00655264,0.00004639963,0.00003180463,0.00008978297,0.002173398,0.00005095158,0.9821974,0.00008283898,0.007109886,0.0004091685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910913,0.000001818656,0.004179209,0.00004279301,0.0007142114,0.001997049,0.0004586754,0.001152275,0.0003627061],"genre_scores_gemma":[0.997281,0.000001549065,0.001186598,0.000127225,0.0004141342,0.0006011917,0.0001855992,0.00008518978,0.0001175695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03485954,"threshold_uncertainty_score":0.9999261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403941607836966,"score_gpt":0.2629380554157574,"score_spread":0.2288986393373877,"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."}}