{"id":"W4412912957","doi":"10.1007/978-981-96-8122-8_7","title":"The Diagnostic Success Story: Diagnostics in the COVID-19 Pandemic: A Triumph of Science and Innovation: Mylab’s Remarkable Role in Transforming Diagnostics During the COVID-19 Pandemic","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Tellabs (Canada)","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Political science; Aeronautics; Medicine; Engineering; Internal medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002137162,0.0007265952,0.0003496197,0.0008746961,0.002825902,0.008981816,0.0009639807,0.005477287,0.02498643],"category_scores_gemma":[0.004533017,0.0002688594,0.0003836943,0.001110367,0.006450629,0.01009926,0.003379298,0.009875154,0.009749901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004151469,"about_ca_system_score_gemma":0.004966516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006151869,"about_ca_topic_score_gemma":0.01205416,"domain_scores_codex":[0.9988438,0.0003533503,0.00002693412,0.0001025345,0.0005482931,0.000125071],"domain_scores_gemma":[0.9977665,0.001490353,0.00007473359,0.00007885698,0.000278198,0.0003114205],"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":[0.00000920845,0.00001345038,0.00005696357,0.00006233765,0.000002257161,0.00005250168,0.0006620613,0.00003899224,0.00009043792,0.1363728,0.8421643,0.02047472],"study_design_scores_gemma":[0.000003203286,0.000005509462,0.00005638402,0.0001113195,0.000001161125,0.00006928049,0.0002847877,0.00003403566,0.00007286941,0.0161198,0.9832368,0.000004806648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007806535,0.08329558,0.00188373,0.390898,0.02760137,0.00003892684,0.000230325,0.000201361,0.49507],"genre_scores_gemma":[0.01752856,0.0514383,0.002652152,0.1873113,0.01457716,0.00008495752,0.0002572551,0.0003862346,0.725764],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02498643,"threshold_uncertainty_score":0.083588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05014395292542447,"score_gpt":0.3391024449335076,"score_spread":0.2889584920080832,"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."}}