{"id":"W3126577929","doi":"10.1257/pandp.20211103","title":"Preparing for a Pandemic: Accelerating Vaccine Availability","year":2021,"lang":"en","type":"article","venue":"AEA Papers and Proceedings","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"","keywords":"Procurement; Pandemic; Portfolio; Incentive; Business; Population; Scale (ratio); Coronavirus disease 2019 (COVID-19); Economics; Finance; Environmental health; Marketing; Disease; Medicine; Microeconomics; Geography; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.00063176,0.0001468277,0.0003321913,0.00005689399,0.0001823728,0.0001603321,0.00009704909,0.0001091471,0.0001654577],"category_scores_gemma":[0.001178183,0.0001639722,0.00007893141,0.000170241,0.00001976757,0.0002790714,0.00009451693,0.0001251104,0.00001491036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009136654,"about_ca_system_score_gemma":0.00003649937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005790139,"about_ca_topic_score_gemma":0.00002895456,"domain_scores_codex":[0.9986889,0.000002065973,0.0004212533,0.0005364578,0.00002806518,0.0003232665],"domain_scores_gemma":[0.9993924,0.0001271402,0.0001849858,0.0001127289,0.00007221222,0.0001105121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004037342,0.00003311018,0.9609604,0.0002979281,0.00004999657,7.092121e-7,0.001633098,0.000002717596,0.00504737,0.02180377,0.002417243,0.007713243],"study_design_scores_gemma":[0.003986931,0.0002547993,0.2555295,0.0001371644,0.00004864956,0.00008493005,0.0009164475,0.005482778,0.003128218,0.04182822,0.687503,0.001099338],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.954883,0.001831254,0.0001253223,0.0008815357,0.0001522555,0.0002978626,0.0000314756,0.00008011151,0.04171719],"genre_scores_gemma":[0.9952893,0.0002864603,0.001599061,0.0012357,0.00013997,0.00005025744,0.000007358257,0.00002251359,0.001369384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7054309,"threshold_uncertainty_score":0.668659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05707650754705978,"score_gpt":0.2689915378371964,"score_spread":0.2119150302901366,"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."}}