File:Logistic regression mixed model results analysing the bees' learning curves to detect SARS-CoV-2.png
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[edit]DescriptionLogistic regression mixed model results analysing the bees' learning curves to detect SARS-CoV-2.png |
English: "Protocol 2
Similar to protocol 1, we analysed the bees’ learning curve during conditioning using a GLMM. A significant interaction (log-odds=−0.26, SE=0.05, Z=−5.48, P<0.001) between treatment and conditioning round was observed, which suggests a significant increase in the bee's discrimination ability between the positive and negative samples with the conditioning rounds (Table 1). By the end of conditioning (round 9) 67 out of 85 (78.8%) bees expressed PER towards infected samples and 23 out of 85 (27.1%) towards healthy samples (Fig. 1C)." See w:Working animal#Pathogens and diseases |
Date | |
Source | https://journals.biologists.com/bio/article/11/4/bio059111/275246/Bees-can-be-trained-to-identify-SARS-CoV-2 |
Author | Authors of the study: Evangelos Kontos, Aria Samimi, Renate W. Hakze-van der Honing, Jan Priem, Aurore Avarguès-Weber, Alexander Haverkamp, Marcel Dicke, Jose L. Gonzales, Wim H. M. van der Poel |
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current | 19:54, 9 September 2023 | 2,161 × 639 (63 KB) | Prototyperspective (talk | contribs) | Uploaded a work by Authors of the study: Evangelos Kontos, Aria Samimi, Renate W. Hakze-van der Honing, Jan Priem, Aurore Avarguès-Weber, Alexander Haverkamp, Marcel Dicke, Jose L. Gonzales, Wim H. M. van der Poel from https://journals.biologists.com/bio/article/11/4/bio059111/275246/Bees-can-be-trained-to-identify-SARS-CoV-2 with UploadWizard |
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