{"id":"W4210590912","doi":"10.1553/ita-ms-20-02","title":"COVID-19 - Voices from Academia (ITA-manu:script 21-02)","year":2021,"lang":"en","type":"report","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preparedness; Multidisciplinary approach; Coronavirus disease 2019 (COVID-19); Pandemic; Consumption (sociology); China; Political science; Public relations; Engineering ethics; Sociology; Engineering; Social science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01212729,0.0005470818,0.000374022,0.00216883,0.002149792,0.007154465,0.001119632,0.002029744,0.1303787],"category_scores_gemma":[0.01975725,0.0002964101,0.0002459389,0.003025848,0.0007326248,0.002763128,0.004271549,0.001501528,0.08289963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002428131,"about_ca_system_score_gemma":0.005687845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006019934,"about_ca_topic_score_gemma":0.007044961,"domain_scores_codex":[0.9944869,0.001963115,0.0003703292,0.0003639476,0.001718407,0.001097371],"domain_scores_gemma":[0.9852943,0.005174649,0.0006640909,0.000942241,0.005735261,0.002189395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006914177,0.0000299438,0.001443469,0.0002047304,0.000002283943,0.0001419484,0.004405608,0.000044746,0.0004466297,0.006437948,0.9435404,0.04323326],"study_design_scores_gemma":[0.000007303317,0.00001032187,0.002299855,0.0001462628,0.000001013534,0.00005279332,0.003446071,0.00005501958,0.0003608882,0.0008785881,0.9927328,0.000009072246],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02104034,0.003999156,0.006482336,0.03680578,0.01100256,0.002134394,0.1099159,0.003893805,0.8047258],"genre_scores_gemma":[0.1314881,0.003058865,0.01450027,0.01136628,0.004617174,0.006090693,0.1030576,0.005153687,0.7206672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9978502,"threshold_uncertainty_score":0.4361603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1500420945893357,"score_gpt":0.3386604169346247,"score_spread":0.188618322345289,"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."}}