{"id":"W4398358802","doi":"10.7910/dvn/mxq8o2","title":"Replication Data for: When do politicians pursue more policy information?","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Replication (statistics); Internet privacy; Political science; Computer science; Computer security; Biology; Virology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008761208,0.0002314232,0.000334219,0.0001642391,0.0004922175,0.0004664264,0.00178284,0.0003641227,0.001520947],"category_scores_gemma":[0.006474782,0.0002399112,0.00007821671,0.0002771682,0.0002090425,0.001709438,0.0004165224,0.0002459274,0.02727254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003356296,"about_ca_system_score_gemma":0.001157166,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05735465,"about_ca_topic_score_gemma":0.005153695,"domain_scores_codex":[0.997456,0.0002049162,0.0005851691,0.0005241205,0.0006013844,0.0006284635],"domain_scores_gemma":[0.9956629,0.0002039237,0.0003589691,0.00310705,0.0002365345,0.0004305732],"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":[0.00001586415,0.00002312403,0.00001099292,0.0001414517,0.0000329573,9.602287e-7,0.0005424941,0.000001130118,7.024692e-7,0.03556082,0.9632424,0.0004271186],"study_design_scores_gemma":[0.0002038724,0.00003757004,0.000026368,0.00005061256,0.0001112053,7.023163e-7,0.000372678,0.00004959007,0.000001711955,0.001793436,0.9970862,0.0002660663],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000003879242,9.135097e-7,0.0002144025,0.002844191,0.0004000884,0.001050348,0.9945534,0.00009056179,0.0008422104],"genre_scores_gemma":[0.0002178536,0.00004479151,0.0001857398,0.003210009,0.002970381,0.00008198009,0.9930276,0.00001466978,0.0002469763],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05220096,"threshold_uncertainty_score":0.9993918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07182061922085753,"score_gpt":0.3811147947378857,"score_spread":0.3092941755170281,"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."}}