{"id":"W2379355143","doi":"","title":"Cooperate with other countries to speedup development of plastic industry in China","year":2002,"lang":"en","type":"article","venue":"Xiandai huagong","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Prairie Improvement Network","funders":"","keywords":"Speedup; China; Business; Computer science; History; Parallel computing; Archaeology","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":[0.001617869,0.001036896,0.0003730808,0.001757416,0.002475238,0.001506951,0.0005764269,0.0008917396,0.0110676],"category_scores_gemma":[0.0009610999,0.0002871742,0.0007403112,0.002275088,0.0004519821,0.0009780965,0.001636558,0.0008044338,0.001662947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003006169,"about_ca_system_score_gemma":0.02037637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02624743,"about_ca_topic_score_gemma":0.02621958,"domain_scores_codex":[0.9993398,0.0001071654,0.00005815647,0.00007433377,0.0001636242,0.0002570363],"domain_scores_gemma":[0.9982162,0.0001115151,0.0001627953,0.0001485656,0.0005919259,0.0007690313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009148892,0.001154904,0.4463229,0.001831182,0.0008987309,0.004579918,0.003661169,0.01008733,0.05391787,0.02507933,0.0953182,0.3562336],"study_design_scores_gemma":[0.0006698407,0.0007676532,0.3567353,0.0001841642,0.0008706477,0.001524423,0.004058392,0.009402152,0.0264885,0.005610862,0.5935641,0.0001239912],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7667225,0.009987617,0.02968914,0.02575631,0.002032068,0.001469164,0.001539398,0.002458499,0.1603454],"genre_scores_gemma":[0.8470556,0.003889362,0.01989448,0.004932385,0.0003502072,0.0003502996,0.002126121,0.000157936,0.1212436],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02624743,"threshold_uncertainty_score":0.05218935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01126854154269947,"score_gpt":0.2288975212134247,"score_spread":0.2176289796707253,"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."}}