{"id":"W2086415300","doi":"10.1007/s11837-006-0175-9","title":"The microstructural characterization of semi-solid slurries","year":2006,"lang":"en","type":"article","venue":"JOM","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Université du Québec","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Slurry; Characterization (materials science); Materials science; Particle-size distribution; Particle (ecology); Particle size; Metallurgy; Microstructure; Mineralogy; Nanotechnology; Composite material; Chemical engineering; Chemistry; Engineering; Geology","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":[0.0001657066,0.0001272544,0.000263093,0.0002870604,0.0003140692,0.0003120236,0.0002177385,0.0002301652,0.001161213],"category_scores_gemma":[0.0006007136,0.0001541131,0.0001155199,0.0002495756,0.0002394459,0.0002626875,0.000152165,0.0002571719,0.0002917573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002639364,"about_ca_system_score_gemma":0.0002212223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453514,"about_ca_topic_score_gemma":0.003598662,"domain_scores_codex":[0.9998572,0.00001047651,0.000009588795,0.00002813167,0.00007870738,0.00001593891],"domain_scores_gemma":[0.9997709,0.00005122972,0.00003960712,0.00002529934,0.00009689417,0.00001603383],"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":[0.00005402555,0.000005539782,0.000445176,0.00002553194,0.000001738314,0.00004575597,0.00004046226,0.0001689973,0.9975961,0.00006357326,0.00003201286,0.001521011],"study_design_scores_gemma":[0.000005855946,0.0001546728,0.01439425,0.000003493175,0.000005185044,0.0001318998,0.000131485,0.002634485,0.9805469,0.00006145251,0.001926614,0.000003773808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943189,0.0002095329,0.00312228,0.00003477505,0.000009496052,0.00001296467,0.0003400539,0.00005476782,0.00189717],"genre_scores_gemma":[0.9963548,0.00006124598,0.002106193,0.00001242085,0.000002815416,0.00001095079,0.0002942199,0.00002080918,0.001136486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001453514,"threshold_uncertainty_score":0.003884673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002733815436532774,"score_gpt":0.170841837450491,"score_spread":0.1681080220139582,"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."}}