{"id":"W6892169692","doi":"10.51408/issi2025_069","title":"Guidance List for Reporting Bibliometric Analyses (GLOBAL): A Two-Round Modified Delphi Study","year":2025,"lang":"en","type":"article","venue":"","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitacs","keywords":"Delphi method; Likert scale; Bibliometrics; Content analysis; Transparency (behavior); Delphi; Inclusion (mineral)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009325378,0.0001487151,0.0003449142,0.00972796,0.0008629675,0.0005817456,0.0008929603,0.00009951908,0.00006964801],"category_scores_gemma":[0.02168813,0.0001368034,0.0001650041,0.09584887,0.0002201057,0.0002951884,0.0002544279,0.0001396358,0.000007114095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004360813,"about_ca_system_score_gemma":0.0005935875,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04056646,"about_ca_topic_score_gemma":0.01520832,"domain_scores_codex":[0.9963245,0.0002960782,0.001159607,0.0005477973,0.001027528,0.00064451],"domain_scores_gemma":[0.9968603,0.0009656134,0.0005299342,0.0005445604,0.0009653426,0.0001343091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000213285,0.002189484,0.5680568,0.0001577134,0.0006257551,0.0001487311,0.002792404,0.000394918,0.002002029,0.1688508,0.1291351,0.1254329],"study_design_scores_gemma":[0.009243401,0.001830555,0.3226099,0.000456062,0.000923529,0.00001391556,0.1822691,0.01748334,0.008464362,0.307348,0.1458411,0.003516678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4468423,0.0006035034,0.1179873,0.003521531,0.0004070648,0.003585312,0.00001639297,0.0008207255,0.4262159],"genre_scores_gemma":[0.9829303,0.00002968245,0.007293277,0.0001843513,0.0001111,0.0004212882,0.000002477706,0.000009642335,0.009017894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.536088,"threshold_uncertainty_score":0.9865526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5081474881378477,"score_gpt":0.6420760984830811,"score_spread":0.1339286103452334,"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."}}