{"id":"W4407216978","doi":"10.1016/j.compmedimag.2025.102503","title":"TQGDNet: Coronary artery calcium deposit detection on computed tomography","year":2025,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital","funders":"","keywords":"Coronary artery calcium; Computed tomography; Calcium; Computer science; Radiology; Medicine; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003944412,0.002131317,0.001131872,0.0018444,0.0003723029,0.0008096614,0.002902922,0.001415371,0.004637129],"category_scores_gemma":[0.00126402,0.000475038,0.0007040573,0.001212305,0.0003278267,0.0006658013,0.001468425,0.000849826,0.002599008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298566,"about_ca_system_score_gemma":0.002023586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03257057,"about_ca_topic_score_gemma":0.04662501,"domain_scores_codex":[0.9996694,0.00002673701,0.00002109649,0.0001263944,0.00009971108,0.00005665821],"domain_scores_gemma":[0.9998106,0.00004252125,0.00002770005,0.00003368472,0.00005528802,0.0000302703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001249976,0.0009033786,0.02967585,0.00139205,0.0005253846,0.00139213,0.0000998042,0.07263094,0.01746123,0.002280108,0.3289665,0.5434226],"study_design_scores_gemma":[0.000404933,0.0004044432,0.02121173,0.0002051474,0.000225081,0.001393618,0.0000832221,0.8847904,0.02377903,0.004190059,0.06320902,0.0001032803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4468164,0.01323317,0.191719,0.003473838,0.001831506,0.002648378,0.1801848,0.1236881,0.03640467],"genre_scores_gemma":[0.5100552,0.004471861,0.165194,0.001723767,0.00044282,0.001523271,0.2935358,0.001058571,0.02199469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03257057,"threshold_uncertainty_score":0.064762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006081829423531283,"score_gpt":0.2302762490481499,"score_spread":0.2241944196246187,"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."}}