{"id":"W2950659211","doi":"10.48550/arxiv.0810.1426","title":"Modeling a Century of Citation Distributions","year":2008,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Citation; Computer science; Environmental science; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005736224,0.0005609738,0.0009947745,0.003973763,0.001088435,0.004249025,0.001820803,0.003126292,0.005497879],"category_scores_gemma":[0.04320098,0.0008015758,0.001045281,0.004891529,0.001702316,0.007271395,0.002074258,0.002634375,0.00119868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003078114,"about_ca_system_score_gemma":0.001110637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01146934,"about_ca_topic_score_gemma":0.006180761,"domain_scores_codex":[0.9984377,0.0005679025,0.00008321082,0.0005624946,0.0001961787,0.0001524946],"domain_scores_gemma":[0.9862669,0.009192412,0.001809523,0.001112397,0.001005149,0.0006135952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002519507,0.0001745568,0.04432233,0.0002314677,0.0002274002,0.0005639557,0.002490951,0.5770261,0.0007611184,0.3186855,0.01017287,0.04509174],"study_design_scores_gemma":[0.00004490816,0.00003636254,0.007242949,0.00005243401,0.0000438995,0.000200703,0.0002288937,0.8008955,0.0001600565,0.1799833,0.01106802,0.00004301963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7292802,0.004532484,0.2240846,0.01159303,0.0004294248,0.0001758345,0.004886205,0.001126955,0.02389137],"genre_scores_gemma":[0.9702851,0.002058789,0.01472579,0.0005140135,0.000358455,0.0002356242,0.001419165,0.0001992954,0.01020377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9960262,"threshold_uncertainty_score":0.03033638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7395991497083269,"score_gpt":0.5638645344195722,"score_spread":0.1757346152887547,"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."}}