{"id":"W4211007133","doi":"10.1007/978-3-319-58380-8_9","title":"Grain Refinement","year":2017,"lang":"fr","type":"book-chapter","venue":"","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Magna International (Canada)","funders":"","keywords":"Materials science; Phase (matter); Alloy; Grain growth; Grain size; Metallurgy; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002890787,0.0007215916,0.0005980748,0.001053147,0.0006862574,0.001045951,0.001430876,0.0006096633,0.04808445],"category_scores_gemma":[0.0005403609,0.0004058873,0.0007984692,0.000885359,0.0006745787,0.001677156,0.00112605,0.001427146,0.02555362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008855091,"about_ca_system_score_gemma":0.0007532911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942089,"about_ca_topic_score_gemma":0.005188686,"domain_scores_codex":[0.9997573,0.00001143787,0.0000108657,0.00007970439,0.0001147946,0.00002587879],"domain_scores_gemma":[0.9998128,0.00001798902,0.000008963992,0.00008100197,0.00007147887,0.000007754958],"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":[0.00008277467,0.00004508294,0.0002870573,0.0004624216,0.00002735699,0.0001156987,0.0002008362,0.008125612,0.04325087,0.2387055,0.07651788,0.6321788],"study_design_scores_gemma":[0.0000178411,0.00005187237,0.0006404928,0.00009388879,0.00003668934,0.0003955373,0.00007987106,0.01213548,0.03782188,0.06694078,0.8817565,0.00002918141],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00907624,0.004752531,0.3452424,0.0008930509,0.001391609,0.0002268212,0.001197487,0.004459339,0.6327606],"genre_scores_gemma":[0.1135487,0.005019866,0.2044548,0.0007126352,0.0003599387,0.0001775735,0.002883239,0.002846559,0.6699967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04808445,"threshold_uncertainty_score":0.1608585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387181847276397,"score_gpt":0.2162988484657092,"score_spread":0.1924270299929453,"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."}}