{"id":"W1974967198","doi":"10.1186/1748-5908-3-49","title":"The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004","year":2008,"lang":"en","type":"article","venue":"Implementation Science","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Vancouver Island University; University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research","keywords":"Citation analysis; Field (mathematics); Sociology of scientific knowledge; Citation; Underpinning; Bibliometrics; Sociology; Data science; Social science; Knowledge management; Computer science; Library science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","sts"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.009315564,0.00009194029,0.0001493691,0.01215163,0.001515183,0.000828479,0.001647983,0.00003001077,0.0002809736],"category_scores_gemma":[0.01965502,0.00004854947,0.00006717363,0.1979725,0.000667532,0.0005762148,0.0002539622,0.0001024751,0.00001401349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000979039,"about_ca_system_score_gemma":0.000408093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001084267,"about_ca_topic_score_gemma":0.001221954,"domain_scores_codex":[0.993484,0.0001964312,0.0005948393,0.0005098152,0.00485882,0.0003560752],"domain_scores_gemma":[0.9919374,0.004263758,0.0002824524,0.0005142066,0.002822252,0.0001799074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003943147,0.00003422513,0.8112409,0.000002840777,0.0000287073,6.520179e-7,0.01226103,0.0002805858,0.007517614,0.001885911,0.01388244,0.1528257],"study_design_scores_gemma":[0.0001869179,0.00009692885,0.9604092,0.000002091335,0.00001342561,0.000004411145,0.00243294,0.003659319,0.02777625,0.001102921,0.004236854,0.00007871209],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598915,0.0002925802,0.0379674,0.0009972599,0.0002555804,0.0003356833,0.0000382321,0.000005772707,0.0002160058],"genre_scores_gemma":[0.9990372,0.00006616329,0.0004654026,0.00008508654,0.00001824396,0.000007884175,0.000002574078,0.000002515975,0.0003149296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1858209,"threshold_uncertainty_score":0.9997847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6583037772825364,"score_gpt":0.6445441319892308,"score_spread":0.01375964529330564,"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."}}