{"id":"W3036281148","doi":"10.18438/eblip29792","title":"Scholarly Publishing During a Pandemic","year":2020,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Global Health and Surgery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Pandemic; Publishing; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Library science; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; World Wide Web; History; Data science; Political science; Medicine; Virology; Law; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008178401,0.0006852853,0.001026553,0.005538302,0.005292046,0.01716246,0.002069718,0.007480474,0.295891],"category_scores_gemma":[0.04086253,0.0005223929,0.00084048,0.006929156,0.002715857,0.01068321,0.007155647,0.006056549,0.1326318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004773183,"about_ca_system_score_gemma":0.009747637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001400458,"about_ca_topic_score_gemma":0.003731195,"domain_scores_codex":[0.9901823,0.001389243,0.000838707,0.0008131531,0.005994777,0.0007818119],"domain_scores_gemma":[0.9571398,0.006215893,0.00237752,0.004577278,0.01900804,0.01068145],"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":[0.00002835137,0.00001730305,0.0002365731,0.0003280611,0.000007028245,0.00009138406,0.0001380325,0.00002431591,0.0002023133,0.008543722,0.944707,0.04567584],"study_design_scores_gemma":[0.000003677428,0.00001083028,0.0003040034,0.0003093514,0.000003345317,0.00006634933,0.0002035466,0.00001261886,0.00007885057,0.001598057,0.9974048,0.000004611929],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00121945,0.02195272,0.0004991438,0.3783761,0.332537,0.0001293473,0.001100334,0.0004791484,0.2637066],"genre_scores_gemma":[0.01244787,0.01822169,0.0006963434,0.06904604,0.08603873,0.000102166,0.001141101,0.0003833614,0.8119227],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9828376,"threshold_uncertainty_score":0.989854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03207309621993246,"score_gpt":0.2821460399390756,"score_spread":0.2500729437191431,"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."}}