{"id":"W4407233220","doi":"10.24294/jipd10176","title":"Exploring the frontiers of artificial intelligence: A bibliometric analysis of high-impact research up to 2023","year":2025,"lang":"en","type":"article","venue":"Journal of Infrastructure Policy and Development","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer 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"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001727822,0.0001044191,0.000481586,0.05450737,0.0001307847,0.00002713346,0.0001718326,0.00006561688,0.00004073506],"category_scores_gemma":[0.002135243,0.00006416139,0.0001142564,0.0718952,0.0001222909,0.0001014662,0.00006314483,0.0003521123,0.000001219301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002847991,"about_ca_system_score_gemma":0.001976237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119611,"about_ca_topic_score_gemma":0.00004665477,"domain_scores_codex":[0.9978704,0.00009287346,0.001088344,0.0001193844,0.0005789185,0.0002500714],"domain_scores_gemma":[0.9976628,0.0004264124,0.0002921083,0.0001727717,0.001267711,0.0001782424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006516333,0.00005311849,0.04229214,0.00009983459,0.001233791,0.000002527451,0.01330889,0.002218422,0.0008372975,0.001247916,0.003648849,0.9344056],"study_design_scores_gemma":[0.00004155892,0.0004106582,0.8989246,0.0002211888,0.0002745686,0.00001305183,0.01349835,0.0001618752,0.07792544,0.006252103,0.002191125,0.00008550903],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984277,0.0005268928,0.01175647,0.002602915,0.0005948065,0.0001737593,0.000004286218,0.000002044812,0.00006184523],"genre_scores_gemma":[0.9935583,0.0006922699,0.005296072,0.0001630141,0.0002221024,0.000006442015,0.000002215286,0.000004687522,0.0000548909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9343201,"threshold_uncertainty_score":0.956209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3082523992583686,"score_gpt":0.5035207817311914,"score_spread":0.1952683824728228,"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."}}