{"id":"W4398293443","doi":"10.7910/dvn/ktwyz6/pvtqzi","title":"pi_pooled_controls.tex","year":2020,"lang":"ca","type":"dataset","venue":"Harvard Dataverse","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Replication (statistics); Asset (computer security); Business; Finance; Computer science; Computer security; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001850919,0.001883192,0.001531081,0.003599595,0.0008010208,0.004097914,0.002676069,0.001827528,0.3766556],"category_scores_gemma":[0.01244379,0.001042771,0.00149278,0.006349488,0.0005005691,0.001464563,0.002420119,0.001703114,0.2809161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284727,"about_ca_system_score_gemma":0.002045219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03222315,"about_ca_topic_score_gemma":0.03335912,"domain_scores_codex":[0.9987418,0.0002340765,0.0001139498,0.0004534715,0.0001987501,0.0002580641],"domain_scores_gemma":[0.9963797,0.0009392892,0.0004800406,0.001165294,0.0007462662,0.0002894316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005283098,0.00001194115,0.0008346856,0.0001750673,0.00004690575,0.000006167106,0.000008370171,0.00007871321,0.00003097083,0.0003938243,0.9963292,0.002031335],"study_design_scores_gemma":[0.000550381,0.00002832954,0.006534658,0.0002802566,0.000101196,0.00003006873,0.00005648607,0.0003025404,0.0003453525,0.001799532,0.9899427,0.00002841902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008648373,0.0000525192,0.0001052576,0.00009699231,0.00004720307,0.00001070997,0.9979844,0.0004118397,0.001204598],"genre_scores_gemma":[0.001223456,0.00008296855,0.0004288953,0.0001410398,0.00007344777,0.0001894428,0.9913139,0.0003888956,0.006157978],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6233444,"threshold_uncertainty_score":0.8891251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278835454936907,"score_gpt":0.2130892650167165,"score_spread":0.2003009104673474,"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."}}