{"id":"W4414326076","doi":"10.69709/caic.2025.129392","title":"Revolutionizing Cardio-Oncology: Utilizing Artificial Intelligence to Build a Cutting-Edge Cancer Registry in Pakistan","year":2025,"lang":"en","type":"article","venue":"Computing&AI Connect","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Cancer registry; Disease; Identification (biology); Cancer; Field (mathematics); Cancer treatment; MEDLINE","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":[0.004081932,0.0002048947,0.0002032567,0.002269357,0.001119456,0.002143093,0.0008730224,0.0004947996,0.003790086],"category_scores_gemma":[0.01156329,0.000271421,0.0003376427,0.002343379,0.0005380576,0.00192307,0.003049532,0.001020755,0.0008674233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002949022,"about_ca_system_score_gemma":0.01776898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05234145,"about_ca_topic_score_gemma":0.04460819,"domain_scores_codex":[0.9985642,0.0005129426,0.0002056516,0.0001995335,0.0002533126,0.0002643095],"domain_scores_gemma":[0.9933182,0.001451666,0.001025705,0.0006822982,0.001788819,0.001733247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002503461,0.0004233699,0.6282762,0.0004549453,0.00009115976,0.002177092,0.003883694,0.006568654,0.001855814,0.007809069,0.04428406,0.3039256],"study_design_scores_gemma":[0.0003363998,0.0007681781,0.5940863,0.00134125,0.0003516296,0.00313074,0.02755973,0.09369615,0.005618608,0.01632184,0.2565565,0.000232534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7655401,0.003245877,0.09910463,0.06681021,0.001242309,0.004218018,0.01651126,0.001939286,0.04138827],"genre_scores_gemma":[0.8738629,0.00279219,0.1085747,0.002941652,0.0002685113,0.0006135549,0.008225245,0.00009220609,0.002628954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05234145,"threshold_uncertainty_score":0.1040736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03594570796065689,"score_gpt":0.396567132637275,"score_spread":0.3606214246766181,"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."}}