{"id":"W4240546189","doi":"10.1007/s11192-006-0097-x","title":"Preface","year":2006,"lang":"en","type":"article","venue":"Scientometrics","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Bibliometrics; Interpretation (philosophy); Citation; Macro; Data science; Citation analysis; Computer science; Scientometrics; Epistemology; Sociology; Management science; Social science; Library science; Philosophy; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","bibliometrics","insufficient_payload"],"category_scores_codex":[0.04056021,0.0001961045,0.0003215265,0.2371088,0.0004506693,0.005520524,0.004318613,0.0001379137,0.00135598],"category_scores_gemma":[0.0639971,0.0001375502,0.000219306,0.7174109,0.0003094824,0.0009544207,0.001013308,0.0002797748,0.004211696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002268043,"about_ca_system_score_gemma":0.0002226987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001824377,"about_ca_topic_score_gemma":0.00001985051,"domain_scores_codex":[0.9709998,0.0001843878,0.0009194348,0.001160194,0.02557269,0.001163503],"domain_scores_gemma":[0.9882336,0.004107932,0.0003108647,0.001385984,0.005362674,0.0005989694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001050652,0.0004090271,0.4820734,0.000004069504,0.000006513895,0.00002681189,0.00004762019,0.0005172449,0.001998855,0.02324445,0.3045644,0.187097],"study_design_scores_gemma":[0.0004197239,0.00009214846,0.5108988,0.000002089178,0.000003515982,0.00001031488,0.00007343903,0.004453352,0.002418191,0.03020575,0.4511456,0.0002770257],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6951882,0.001926235,0.03157675,0.001200713,0.002434995,0.0003681535,0.00005389798,0.0001569882,0.2670941],"genre_scores_gemma":[0.9545873,0.00003097919,0.003501415,0.0001367848,0.0002121069,0.00000808466,0.000005776937,0.00001446763,0.04150311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4803021,"threshold_uncertainty_score":0.9995569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6899883062376743,"score_gpt":0.6221987966117799,"score_spread":0.06778950962589436,"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."}}