{"id":"W4399001747","doi":"10.7910/dvn/yiqkn8","title":"Replication Data for: Transformed-Likelihood Estimators for Dynamic Panel Models with a Very Small T","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Replication (statistics); Estimator; Panel data; Computer science; Econometrics; Statistics; Mathematics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006319925,0.0005045525,0.001061624,0.0003239583,0.0001941741,0.0002152936,0.002382465,0.0003456186,0.0007752361],"category_scores_gemma":[0.0003982616,0.0005277981,0.0002396477,0.0003190296,0.00007435598,0.0008911134,0.0003315017,0.0002734904,0.00728892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001319078,"about_ca_system_score_gemma":0.0001592241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001601672,"about_ca_topic_score_gemma":0.002250051,"domain_scores_codex":[0.9963887,0.00001516307,0.0009638658,0.002018922,0.00008881614,0.0005244891],"domain_scores_gemma":[0.9932278,0.0001641262,0.0007428721,0.0055565,0.00007334545,0.0002353877],"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":[0.0003186268,0.00009012151,0.00002012906,0.0006103439,0.0005359736,0.000005766323,0.00002601722,0.0002028333,7.680888e-7,0.0008993011,0.9964571,0.0008329988],"study_design_scores_gemma":[0.001113781,0.000165263,0.00001202187,0.00005739972,0.0005251745,0.000005673263,0.00002655067,0.1267845,0.000001648485,0.003138885,0.8675654,0.0006037662],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001023216,0.00001421741,0.2325065,0.00005230214,0.0001937797,0.001072371,0.7660641,0.00004806983,0.00003849795],"genre_scores_gemma":[0.0000885403,0.001184369,0.01207105,0.0004841568,0.0001805925,0.0004488183,0.9854079,0.00007615619,0.00005835144],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2204354,"threshold_uncertainty_score":0.9997174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1034399513871938,"score_gpt":0.2544787240763848,"score_spread":0.1510387726891911,"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."}}