{"id":"W3034475429","doi":"","title":"Mathematics ≠ Science: A study in citation rates over time","year":2019,"lang":"en","type":"article","venue":"Deep Blue (University of Michigan)","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Mathematics; Mathematics education; Computer science; Library science","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":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics","insufficient_payload"],"consensus_categories":["bibliometrics","insufficient_payload"],"category_scores_codex":[0.01134689,0.00008764867,0.0002751663,0.03529622,0.0001567849,0.0003119202,0.002072622,0.00005502825,0.001395802],"category_scores_gemma":[0.002842434,0.00008123445,0.00007123664,0.1053548,0.0002571595,0.0009069466,0.000617678,0.0001434347,0.001531405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006919859,"about_ca_system_score_gemma":0.000181318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001107453,"about_ca_topic_score_gemma":0.00156042,"domain_scores_codex":[0.9941704,0.00009944585,0.0002625631,0.0004928404,0.004649088,0.0003256937],"domain_scores_gemma":[0.9967461,0.001192404,0.0002139136,0.0005469193,0.001152425,0.0001482525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001497503,0.003196317,0.6014586,0.00003932138,0.00005868102,0.00008412563,0.3147578,0.001080373,0.05255324,0.00228574,0.0003506777,0.02398534],"study_design_scores_gemma":[0.001613875,0.0003468835,0.6886344,0.00001359575,0.00000845322,0.000001900828,0.2066563,0.09913317,0.0003809489,0.002716207,0.0003027469,0.0001914772],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960697,0.00003448664,0.0005590047,0.00007727022,0.0001093214,0.0003775805,0.000006669681,0.000009967624,0.002755991],"genre_scores_gemma":[0.9958014,0.000007823416,0.001520298,0.00001266383,0.000005534676,1.26652e-7,0.000001140545,0.000004116261,0.002646822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1081015,"threshold_uncertainty_score":0.9995171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2270113176776836,"score_gpt":0.4646095983762427,"score_spread":0.2375982806985592,"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."}}