{"id":"W2518333632","doi":"10.5539/jas.v8n10p73","title":"Few Journal Article Organizational Structure Characteristics Affect Article Citation Rate: A Look at Agricultural Economics Articles Using Regression Analysis","year":2016,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Salary; Tobit model; Organizational structure; Variables; Regression analysis; Psychology; Social science; Econometrics; Economics; Management; Statistics; Sociology; Mathematics; Computer science; Library science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.008222881,0.0002991839,0.0004997017,0.009039018,0.0004837317,0.002329583,0.0006585282,0.0005523191,0.002510902],"category_scores_gemma":[0.05030563,0.0002641726,0.001807416,0.01065279,0.0005231226,0.001828963,0.0007129466,0.0007192882,0.001037134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006893257,"about_ca_system_score_gemma":0.001110251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004684051,"about_ca_topic_score_gemma":0.008122768,"domain_scores_codex":[0.9938132,0.00242287,0.0009701892,0.000612386,0.001841556,0.0003399268],"domain_scores_gemma":[0.8554094,0.08989887,0.03301171,0.006516004,0.01334104,0.001822948],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005318679,0.00008124353,0.9796648,0.00009783266,0.0004193647,0.0000588832,0.0004430657,0.0004424359,0.000633034,0.0002298245,0.0003695132,0.01750682],"study_design_scores_gemma":[0.000003802778,0.0001030422,0.9949066,0.00004929505,0.0001750841,0.0000709203,0.0007883526,0.00167669,0.0007196577,0.0002042007,0.001286075,0.00001625671],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919614,0.0009909642,0.001623639,0.0004319622,0.0000236874,0.000028782,0.0005464285,0.00005293619,0.004340252],"genre_scores_gemma":[0.9966799,0.0004512102,0.00110673,0.00006003561,0.00005243035,0.00001779493,0.0007671092,0.0000432332,0.0008215369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9917771,"threshold_uncertainty_score":0.04348725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1673979953051462,"score_gpt":0.4343439875418311,"score_spread":0.2669459922366849,"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."}}