{"id":"W2351685470","doi":"","title":"A bibliometrical analysis of competitive situation in international ecological research","year":2011,"lang":"en","type":"article","venue":"Soil and Environmental Sciences","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Ecology; Geography; Political science; Environmental resource management; Regional science; Environmental science; Biology","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":[0.01379472,0.0004918571,0.001071083,0.1554787,0.002416312,0.006811088,0.0009695062,0.0007085132,0.00443606],"category_scores_gemma":[0.08296001,0.0002742148,0.001255536,0.211786,0.001380721,0.005944984,0.002864819,0.0006057249,0.0005410807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003584068,"about_ca_system_score_gemma":0.003199741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005134664,"about_ca_topic_score_gemma":0.005578722,"domain_scores_codex":[0.9743611,0.00654126,0.005452176,0.001591475,0.01105039,0.001003546],"domain_scores_gemma":[0.9071041,0.05561883,0.01428877,0.003360423,0.01727219,0.002355642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002711188,0.0001837614,0.789086,0.00325687,0.0008757868,0.0006416954,0.006094127,0.001678268,0.001511905,0.02045734,0.01363244,0.1623107],"study_design_scores_gemma":[0.00005562091,0.0001856392,0.9114887,0.0006420334,0.0007313319,0.001403661,0.01586476,0.01094099,0.001026871,0.01334359,0.04418556,0.0001313405],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8472524,0.01477923,0.01033845,0.002925362,0.0003154614,0.0008300547,0.02679844,0.0006794035,0.09608119],"genre_scores_gemma":[0.9805547,0.002438673,0.007423454,0.00005318624,0.0001435841,0.0003861472,0.007535392,0.00004574986,0.001419164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8445213,"threshold_uncertainty_score":0.0729543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1359711661426558,"score_gpt":0.3332676360158532,"score_spread":0.1972964698731974,"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."}}