{"id":"W7055116152","doi":"","title":"Biopharmaceuticals, Financialization &amp; Nationalism in the Age of COVID-19","year":2021,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); State (computer science); Nationalism; Financialization; Raising (metalworking); Politics; Gloom","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002061504,0.00007245323,0.00009199746,0.00003196269,0.00005630902,0.00003187162,0.0001458905,0.00005472416,0.0002851341],"category_scores_gemma":[0.0001508077,0.0000644497,0.00003598036,0.0004347283,0.00003869832,0.00007172636,0.00001636184,0.0001186379,0.00008683554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005384551,"about_ca_system_score_gemma":0.00007453112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001244888,"about_ca_topic_score_gemma":0.0006987907,"domain_scores_codex":[0.9993593,0.0000596565,0.000193887,0.000111869,0.0001603418,0.0001150039],"domain_scores_gemma":[0.9995406,0.0001181507,0.00001889283,0.0002207914,0.0000407323,0.00006083435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005444489,0.000127978,0.0008113306,0.0001782928,0.00002170075,0.00003285284,0.0006753004,0.01708846,0.05437725,0.9005669,0.02588534,0.0002291216],"study_design_scores_gemma":[0.0003712081,0.00000252724,0.001848274,0.00001370761,0.0000115699,0.000007085328,0.00003881424,0.001049309,0.005872255,0.01096584,0.9797071,0.0001123734],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5392535,0.01231494,0.3085606,0.02585213,0.001529596,0.002594024,0.0008789538,0.001216387,0.1077999],"genre_scores_gemma":[0.993883,0.0001766011,0.001433526,0.003318001,0.0001023222,0.0000850715,0.0003019762,0.00001586707,0.0006836554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9538217,"threshold_uncertainty_score":0.3122019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03967293560713041,"score_gpt":0.3002851058663316,"score_spread":0.2606121702592011,"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."}}