{"id":"W2531925341","doi":"","title":"玛格纳（Magna）宣布在英国建最先进的铝合金压铸厂","year":2016,"lang":"zh","type":"article","venue":"铸造","topic":"Metallurgy and Material Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001278642,0.0002817755,0.0003423657,0.00006934001,0.0002886073,0.0002328837,0.0008744576,0.0001767945,0.0448423],"category_scores_gemma":[0.0003457401,0.0001711916,0.0001056742,0.0002314904,0.000522237,0.0006175052,0.0003521039,0.00006570239,0.03121452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007958213,"about_ca_system_score_gemma":0.0001712855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001634641,"about_ca_topic_score_gemma":0.00004408768,"domain_scores_codex":[0.9972044,0.0002156612,0.000445773,0.0007304372,0.0005612756,0.0008424353],"domain_scores_gemma":[0.9985013,0.0001418771,0.0001979265,0.0007261404,0.00009160805,0.0003411567],"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":[0.0000481336,0.00006322428,0.0000960789,0.00003039418,0.000005817008,0.00003039862,0.0001547615,8.606915e-7,0.9253656,0.06010224,0.003955749,0.01014677],"study_design_scores_gemma":[0.001305072,0.0004124374,0.005669057,0.000432227,0.00006752949,0.00005109329,0.00007501963,0.0000193677,0.5301707,0.03201187,0.4287704,0.001015288],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8075436,0.0004531316,0.002756158,0.006240903,0.01439695,0.000446764,0.0001281423,0.0002521453,0.1677822],"genre_scores_gemma":[0.9549689,0.0002636694,0.0008084546,0.0004880345,0.0007296849,0.00001686462,0.000001312476,0.00002161148,0.04270145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4248146,"threshold_uncertainty_score":0.9695398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356277332287566,"score_gpt":0.251497554913271,"score_spread":0.2279347815903954,"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."}}