{"id":"W4408074120","doi":"10.51594/csitrj.v6i2.1818","title":"AI and data-driven innovations in healthcare: Enhancing cancer detection, workforce optimization, and comprehensive care for people living with HIV","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Child, Adolescent and Family Mental Health","funders":"","keywords":"Workforce; Health care; Human immunodeficiency virus (HIV); Cancer; Nursing; Medicine; Business; Political science; Family 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001485084,0.000101453,0.0002746609,0.0009059391,0.001033202,0.0007134473,0.0004610974,0.00004924664,0.000006823323],"category_scores_gemma":[0.0002247728,0.0001044391,0.00001404195,0.001387559,0.0003313498,0.001332896,0.0003570291,0.000404383,9.117055e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003959636,"about_ca_system_score_gemma":0.0007432406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004465983,"about_ca_topic_score_gemma":0.002466573,"domain_scores_codex":[0.9984924,0.00002487626,0.0004321955,0.0004950688,0.00008229705,0.0004731324],"domain_scores_gemma":[0.998433,0.0001776183,0.0001605381,0.0002612973,0.0008319485,0.0001356099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009700901,0.00008077989,0.6151716,0.0004439721,0.00006343029,0.000005375633,0.01062832,0.1659434,0.00007128745,0.0563814,0.003505387,0.1476081],"study_design_scores_gemma":[0.001271726,0.0002755209,0.1885584,0.000857597,0.000004683789,0.00003821101,0.001057138,0.7916935,0.00005404774,0.004517192,0.01132915,0.0003428496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1102768,0.004214899,0.8727186,0.01191499,0.0003351592,0.0003743788,0.00004353332,0.00000902817,0.0001126583],"genre_scores_gemma":[0.9815214,0.001747318,0.01543066,0.001006212,0.000183287,0.00003342683,0.000004091151,0.000009633402,0.0000639608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8712447,"threshold_uncertainty_score":0.7946661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0725394133560295,"score_gpt":0.3676889888363398,"score_spread":0.2951495754803103,"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."}}