{"id":"W2921565448","doi":"10.1007/s11192-019-03066-3","title":"What characterises funded biomedical research? Evidence from a basic and a clinical domain","year":2019,"lang":"en","type":"article","venue":"Scientometrics","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Health Canada; National Cancer Institute; Consejo Superior de Investigaciones Científicas; National Institutes of Health; Impact Fund; Ministerio de Economía y Competitividad; European Commission; National Research Centre; Nature","keywords":"Basic research; Public funding; Political science; Institution; Public domain; Public institution; Public relations; Public administration; Library science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.114416,0.0009116424,0.003884741,0.04186803,0.001498382,0.01297027,0.003651035,0.004158739,0.005657708],"category_scores_gemma":[0.3806741,0.0007407155,0.003947281,0.05480352,0.008081115,0.009932451,0.00630276,0.002072503,0.0009707526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00689615,"about_ca_system_score_gemma":0.0124875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004350304,"about_ca_topic_score_gemma":0.005798811,"domain_scores_codex":[0.8501409,0.08150322,0.02850771,0.006680686,0.02992002,0.003247445],"domain_scores_gemma":[0.308394,0.5329807,0.09818511,0.01971877,0.03265061,0.00807076],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002898439,0.0004522898,0.675184,0.03046431,0.01204769,0.0005094142,0.004737148,0.001247994,0.0004848367,0.03418166,0.008250018,0.2295422],"study_design_scores_gemma":[0.0005733783,0.0009656596,0.8356738,0.0257634,0.007719717,0.00254721,0.01001672,0.001907354,0.0009274532,0.06243085,0.05125981,0.0002146645],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4179406,0.439354,0.01098659,0.07960161,0.001872616,0.0005763971,0.006610511,0.0001000619,0.04295767],"genre_scores_gemma":[0.9406457,0.04588597,0.004179148,0.004656815,0.001557701,0.0002649121,0.002146658,0.00003831397,0.0006247972],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.958132,"threshold_uncertainty_score":0.6050969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8248587450899906,"score_gpt":0.6784602035793619,"score_spread":0.1463985415106287,"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."}}