{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003982631,0.001536422,0.001176073,0.00328443,0.000848164,0.002460828,0.00355288,0.002249944,0.1156051],"category_scores_gemma":[0.02532018,0.0009229053,0.001246053,0.006405356,0.0004944567,0.001656439,0.002070775,0.002054828,0.1200296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301853,"about_ca_system_score_gemma":0.002759043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02547482,"about_ca_topic_score_gemma":0.04089733,"domain_scores_codex":[0.9974185,0.0006425207,0.0004804417,0.00059184,0.000612157,0.000254488],"domain_scores_gemma":[0.9896631,0.002727047,0.001033628,0.003274205,0.002911565,0.0003905527],"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":[0.00006969508,0.00002357065,0.001319251,0.0003732175,0.00002940324,0.00002710338,0.00002329258,0.0002499697,0.0000670012,0.0009754914,0.9931797,0.003662266],"study_design_scores_gemma":[0.0005703431,0.00002534581,0.006975572,0.0003289789,0.00003632254,0.00009170944,0.00009869933,0.0005353912,0.0003791233,0.002948408,0.9879673,0.00004284448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002179399,0.00005939736,0.0004774641,0.0001006113,0.00004468684,0.00003857118,0.9975165,0.0005164415,0.00102841],"genre_scores_gemma":[0.0009615747,0.00006263655,0.001718187,0.0000846819,0.0000179014,0.0003486183,0.9951692,0.0001813052,0.001455875],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1156051,"threshold_uncertainty_score":0.3867375,"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."}}