{"id":"W6959347145","doi":"10.7685/jnau.201809016","title":"基于Scopus的植物表型组学研究进展分析","year":2018,"lang":"en","type":"article","venue":"UEA Digital Repository (University of East Anglia)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chinese academy of sciences; Bibliometrics; China; Scientometrics; Scopus; Citation; Statistical analysis; Basic research","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01548673,0.001574088,0.002820519,0.1238274,0.002166414,0.01072306,0.002003394,0.001542814,0.02781905],"category_scores_gemma":[0.0761727,0.0006411536,0.001592759,0.1839442,0.001297556,0.00682245,0.003956273,0.001180379,0.01070307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00424119,"about_ca_system_score_gemma":0.02542988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01031097,"about_ca_topic_score_gemma":0.01126463,"domain_scores_codex":[0.982955,0.003036468,0.00605451,0.001161245,0.006096674,0.0006961388],"domain_scores_gemma":[0.9048937,0.0374533,0.01754673,0.005671015,0.03100977,0.003425462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00048986,0.00009597632,0.01863331,0.1679395,0.001502242,0.0009741529,0.001884258,0.001374504,0.00204192,0.02852534,0.2260036,0.5505353],"study_design_scores_gemma":[0.00010707,0.0002062909,0.04636023,0.06934983,0.002428663,0.001015697,0.003293374,0.002031999,0.002673219,0.02812694,0.8441235,0.0002832143],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04532448,0.2027358,0.02302407,0.02109282,0.005322624,0.007263526,0.4523077,0.006043839,0.236885],"genre_scores_gemma":[0.2207127,0.3765066,0.1090634,0.003471814,0.004214859,0.007747285,0.2502895,0.001755218,0.02623859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8761725,"threshold_uncertainty_score":0.09306395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135200639470876,"score_gpt":0.1806907751249115,"score_spread":0.1671707111778239,"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."}}