{"id":"W2766309470","doi":"10.2139/ssrn.3056433","title":"Technology and Return Predictability","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; McMaster University","funders":"","keywords":"Predictability; Business; Economics; Econometrics; Mathematics; Statistics","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":[0.00425389,0.0002704505,0.000462671,0.002222801,0.002189172,0.01002296,0.0007277934,0.003312717,0.02111882],"category_scores_gemma":[0.05870853,0.0002710551,0.0004522852,0.001680285,0.005458428,0.007359482,0.002825509,0.004894678,0.001827973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003176395,"about_ca_system_score_gemma":0.003211785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004398628,"about_ca_topic_score_gemma":0.003248144,"domain_scores_codex":[0.9964395,0.001101429,0.0001940116,0.0004500956,0.0009489615,0.000865982],"domain_scores_gemma":[0.9523369,0.03399846,0.006926224,0.0023363,0.002604873,0.001797259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001847419,0.0001220732,0.04095131,0.00005196702,0.00005011021,0.000654261,0.002373703,0.003714793,0.0001305062,0.8946908,0.01794523,0.03913056],"study_design_scores_gemma":[0.00003744846,0.00009809058,0.02230186,0.0001355117,0.0000517921,0.0003516185,0.003261671,0.004310966,0.000290172,0.9359666,0.03314312,0.00005126961],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2940591,0.007453851,0.01469952,0.1261474,0.001188086,0.00007536919,0.0005733955,0.0002487714,0.5555543],"genre_scores_gemma":[0.9887819,0.0007995818,0.0002742561,0.001724133,0.0006814927,0.00001578617,0.00004153565,0.00003513298,0.007646151],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02111882,"threshold_uncertainty_score":0.0706495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007876040918666609,"score_gpt":0.2672354152775819,"score_spread":0.2593593743589153,"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."}}