{"id":"W2405999279","doi":"10.1016/j.powtec.2016.05.046","title":"Improvement of flow of an iron-copper-graphite powder mix through additions of nanoparticles","year":2016,"lang":"en","type":"article","venue":"Powder Technology","topic":"Injection Molding Process and Properties","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Rio Tinto (Canada); National Research Council Canada; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lubricant; Nanoparticle; Copper; Materials science; Carbon black; Graphite; Ferrous; Mixing (physics); Powder metallurgy; Chemical engineering; Metallurgy; Composite material; Sintering; Nanotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002639236,0.0003037665,0.0002124058,0.0003885836,0.0002018429,0.0003327349,0.0002171136,0.0003564906,0.001225315],"category_scores_gemma":[0.0002710236,0.0001796962,0.0002354032,0.0002469212,0.0001691856,0.0003860864,0.0001297357,0.0003640939,0.0002403595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002197207,"about_ca_system_score_gemma":0.0002383923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004085269,"about_ca_topic_score_gemma":0.0007371071,"domain_scores_codex":[0.9998447,0.00001769867,0.00001469783,0.0000381299,0.0000646148,0.00002020299],"domain_scores_gemma":[0.999897,0.00002842063,0.00003408658,0.0000105934,0.00001734416,0.00001250534],"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":[0.0001505197,0.00003208069,0.00014487,0.00004730064,0.000002452925,0.00002816999,0.00001980244,0.0001184733,0.9967834,0.000128075,0.00002988422,0.002514949],"study_design_scores_gemma":[0.000005641064,0.00007129984,0.000404082,0.000001824044,0.00000373428,0.0000121492,0.000003774266,0.0008121886,0.9983687,0.000008881896,0.0003061173,0.000001748914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889264,0.0004153533,0.007745504,0.00007916956,0.0000354956,0.00004986776,0.0001292741,0.0003226321,0.002296199],"genre_scores_gemma":[0.99217,0.0001755201,0.00571452,0.0000121681,0.00001047872,0.00002317038,0.00008546402,0.0000324537,0.00177612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001225315,"threshold_uncertainty_score":0.004099131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009832327986765874,"score_gpt":0.2137986428744658,"score_spread":0.2039663148876999,"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."}}