{"id":"W7130596087","doi":"10.1109/icec2nt65402.2025.11380054","title":"Dueling Double Deep Q-Networks for Regime-Aware and Risk-Conscious Stock Trading: Evidence from NIFTY 50","year":2025,"lang":"","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Reinforcement learning; Sharpe ratio; Stock market; Profitability index; Stock exchange; Database transaction; Volatility (finance); Stock market index; Markov chain","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02014609,0.000991659,0.001749299,0.0008882769,0.002254237,0.002252589,0.002492359,0.0008683021,0.001257797],"category_scores_gemma":[0.0301905,0.0008556235,0.0006610804,0.002590194,0.000780111,0.001202591,0.001137867,0.001171401,0.00002595992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002644271,"about_ca_system_score_gemma":0.0006833547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002382989,"about_ca_topic_score_gemma":0.001800991,"domain_scores_codex":[0.9888343,0.001792261,0.002788818,0.003450838,0.001554213,0.001579599],"domain_scores_gemma":[0.9190854,0.07561452,0.001393841,0.002228924,0.001051812,0.0006255416],"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":[0.002887313,0.0001116175,0.1405179,0.00009082756,0.0004249103,0.00001256414,0.001506706,0.004952462,0.00005585666,0.0005512008,0.02442848,0.8244601],"study_design_scores_gemma":[0.003281247,0.000343821,0.0135827,0.001574794,0.0007924294,0.00001505667,0.001794522,0.9187182,0.0003896832,0.05095373,0.007552005,0.001001866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0939151,0.02466783,0.8661572,0.001165125,0.006336674,0.002588605,0.00004452926,0.0002136154,0.004911373],"genre_scores_gemma":[0.7298713,0.001838574,0.2528559,0.000379526,0.0006055147,0.0002265198,0.000005625715,0.00007897582,0.01413807],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9137657,"threshold_uncertainty_score":0.9996552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1321848584319325,"score_gpt":0.406342407047304,"score_spread":0.2741575486153715,"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."}}