{"id":"W4415774836","doi":"10.71000/yt67zy08","title":"ROLE OF AI IN PREDICTING CARDIOVASCULAR RISK USING ROUTINE DENTAL IMAGING: A SYSTEMATIC REVIEW","year":2025,"lang":"","type":"article","venue":"Insights-Journal of Life and Social Sciences","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Systematic review; MEDLINE; Risk assessment; Prospective cohort study; Subclinical infection; Disease; Coronary artery disease; Cochrane Library; Predictive value of tests","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":[],"consensus_categories":[],"category_scores_codex":[0.004735164,0.0002902406,0.001877633,0.0007738607,0.0008168915,0.0003412071,0.0006268024,0.00008918452,0.000008961015],"category_scores_gemma":[0.0007027031,0.0002356547,0.001156744,0.002130067,0.0009989865,0.001261947,0.000188246,0.0006318323,8.120679e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225856,"about_ca_system_score_gemma":0.0006008672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007521411,"about_ca_topic_score_gemma":0.00005938723,"domain_scores_codex":[0.994472,0.001113074,0.002311732,0.0003557278,0.001341789,0.0004056367],"domain_scores_gemma":[0.997384,0.0002381049,0.001764341,0.0001686991,0.0003271232,0.0001177723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00005556084,0.0002775938,0.9177017,0.07012687,0.001844291,0.0001860536,0.007218639,0.0001421803,0.0005321144,0.0006418283,0.00007812824,0.001195095],"study_design_scores_gemma":[0.00679126,0.0004643359,0.1985359,0.5897898,0.01940305,0.001627812,0.1426711,0.03137075,0.0007707524,0.006461114,0.0004447043,0.001669392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.558307,0.4400933,0.0001497143,0.0001080181,0.0005658161,0.0002968199,0.000006053465,0.000003733461,0.0004695453],"genre_scores_gemma":[0.9844571,0.01474154,0.00009501119,0.0004565908,0.0002302345,0.000002436536,3.327469e-7,0.000009015196,0.000007749074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7191657,"threshold_uncertainty_score":0.9609722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01616549173604048,"score_gpt":0.2970086077444364,"score_spread":0.2808431160083959,"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."}}