{"id":"W4402055545","doi":"10.18280/acsm.480404","title":"Mapping Publications of Cracks Monitoring in Concrete Structures: Bibliometric and Scientometric Review in 2013-2023","year":2024,"lang":"en","type":"article","venue":"Annales de Chimie Science des Matériaux","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Bibliometrics; Environmental science; Engineering; Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001455023,0.0001572576,0.0002450175,0.03795284,0.00008468441,0.0002371141,0.0004125282,0.00005515816,0.00001868034],"category_scores_gemma":[0.0005944077,0.0001448095,0.00004101202,0.1074502,0.0003720256,0.0008849975,0.0001041672,0.0002695848,0.000006958279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002287268,"about_ca_system_score_gemma":0.0001493553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007159336,"about_ca_topic_score_gemma":0.000008722627,"domain_scores_codex":[0.9983341,0.0000198259,0.000393305,0.0003213207,0.0003780419,0.0005534406],"domain_scores_gemma":[0.9993429,0.000130368,0.00004298523,0.0002308939,0.0001298884,0.0001229644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009524245,0.00002071703,0.5371742,0.02095268,0.00007320692,0.00008194014,0.006714056,0.01611184,0.1076649,0.006410553,0.003424952,0.3013614],"study_design_scores_gemma":[0.0001753758,0.0000249111,0.9660355,0.005420573,0.00001069031,0.0000613108,0.0005508868,0.01707653,0.005543353,0.002300133,0.002469868,0.0003308725],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9159582,0.08072608,0.001068127,0.0001061382,0.0006489059,0.0002122842,0.000008471035,0.0001050821,0.001166761],"genre_scores_gemma":[0.958831,0.03676778,0.004231835,0.00001608822,0.00008481451,0.0000245262,0.000001624055,0.00001631716,0.00002607234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4288613,"threshold_uncertainty_score":0.9729512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03985074345792553,"score_gpt":0.312533120152986,"score_spread":0.2726823766950604,"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."}}