{"id":"W2386536224","doi":"","title":"Science funding and SCI papers output: a comparative analysis on 10 countries","year":2013,"lang":"en","type":"article","venue":"Kexuexue yanjiu","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Funding Agency; Agency (philosophy); Political science; Publishing; Regional science; Business; Library science; Economic growth; Geography; Economics; Sociology; Social science; Public relations","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.004806257,0.0004160747,0.0008986926,0.01498079,0.000597238,0.003429816,0.0005027237,0.0004895803,0.003967682],"category_scores_gemma":[0.0194413,0.0002338859,0.001405611,0.03246186,0.0006557545,0.001930187,0.001508079,0.0003572311,0.0007173838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149337,"about_ca_system_score_gemma":0.001250202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003976624,"about_ca_topic_score_gemma":0.003595006,"domain_scores_codex":[0.994916,0.001435643,0.0009122936,0.0005695705,0.001325503,0.00084103],"domain_scores_gemma":[0.9727249,0.009590295,0.01006373,0.0009726171,0.004747799,0.001900727],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006351845,0.00006678853,0.9595087,0.0008131792,0.0009882178,0.0007644366,0.0006442287,0.001671652,0.0005804514,0.001549415,0.001951265,0.03082661],"study_design_scores_gemma":[0.00003075373,0.00009948105,0.9908869,0.00009723441,0.0003738483,0.0003310168,0.001766415,0.0004916848,0.0003535301,0.0002335729,0.00531391,0.00002167591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9735473,0.007269455,0.0004295159,0.0003649799,0.00003985607,0.0000321566,0.007076771,0.00006121094,0.01117885],"genre_scores_gemma":[0.9898178,0.003127719,0.0003200089,0.00004055275,0.00004806104,0.00004562686,0.005385378,0.00002076364,0.001194122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9951937,"threshold_uncertainty_score":0.02541816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386727030835912,"score_gpt":0.2247321581371789,"score_spread":0.2108648878288198,"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."}}