{"id":"W2048452064","doi":"10.1145/2628194.2628211","title":"A machine learning approach for stock price prediction","year":2014,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Oracle; Computer science; Machine learning; Artificial intelligence; Support vector machine; Decision tree; Inference; Graph; Decision support system; Data mining; Theoretical computer science","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"],"consensus_categories":[],"category_scores_codex":[0.01396987,0.0001259386,0.0002356193,0.0002182367,0.0002660237,0.000157202,0.0004773584,0.00007984581,0.0002753736],"category_scores_gemma":[0.03256787,0.00008602137,0.0001182198,0.0005688604,0.00003921463,0.0001759783,0.0001191638,0.0001713173,0.00003452714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002750344,"about_ca_system_score_gemma":0.00001914906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001530617,"about_ca_topic_score_gemma":0.000002157687,"domain_scores_codex":[0.997287,0.000641365,0.0004571997,0.0005333431,0.0008087846,0.0002723324],"domain_scores_gemma":[0.9939842,0.005024187,0.0002066249,0.0004153526,0.0002638718,0.0001057292],"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":[0.0001340469,0.00006491961,0.03500704,0.00001293151,0.0000160487,1.01683e-7,0.0002706451,0.007311437,0.0003756371,0.005531013,0.009878619,0.9413975],"study_design_scores_gemma":[0.0003757629,0.0001966486,0.008065638,0.000002557571,0.000007727034,0.000008567565,0.00006433099,0.8659797,0.0001029586,0.008932944,0.1161672,0.00009600105],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005217338,0.00001633995,0.8019325,0.00008563275,0.0002348572,0.0003203382,0.00000400864,0.0001587806,0.1920303],"genre_scores_gemma":[0.3588995,7.049217e-7,0.6055276,0.0001133509,0.0002339633,0.00008362289,0.000009482344,0.00002008814,0.03511166],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9413016,"threshold_uncertainty_score":0.9755812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1349466357588076,"score_gpt":0.3893020969692675,"score_spread":0.25435546121046,"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."}}