{"id":"W6991115291","doi":"","title":"Financial trading systems - neural and genetic algorithms","year":2003,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetic algorithm; Artificial neural network; Inheritance (genetic algorithm); Order (exchange); Reproduction; Control (management)","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":["metaresearch","metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.007236834,0.001173299,0.001704633,0.00126589,0.001898793,0.0008238186,0.001688031,0.001279009,0.0003025433],"category_scores_gemma":[0.02613688,0.001097,0.0005237906,0.001912241,0.0001426068,0.0008310315,0.000196436,0.002021978,0.0001671488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004541043,"about_ca_system_score_gemma":0.0001402625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001946435,"about_ca_topic_score_gemma":0.0002416661,"domain_scores_codex":[0.9876136,0.002887584,0.002464546,0.002587031,0.003218016,0.001229269],"domain_scores_gemma":[0.9918239,0.003688115,0.001580763,0.001453546,0.0008754561,0.0005782736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001872873,0.00008686118,0.000250803,0.0001909062,0.00008643261,0.0002931924,0.00002047929,0.0001112234,0.004481835,0.01186911,0.0001033191,0.9823185],"study_design_scores_gemma":[0.007467029,0.002053565,0.09373945,0.002891007,0.00174615,0.004371278,0.002998271,0.02849946,0.02025942,0.4352232,0.3880643,0.01268689],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9242643,0.001689792,0.00001163133,0.000008127169,0.01003616,0.001063607,0.0005807299,0.0002056534,0.06214],"genre_scores_gemma":[0.9446282,0.0001347739,0.0151809,0.0002148792,0.0002926606,0.0002708378,0.0001436903,0.0003683313,0.03876574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9696317,"threshold_uncertainty_score":0.9994006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07047883618678386,"score_gpt":0.336938551814384,"score_spread":0.2664597156276001,"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."}}