Classes of errors and gaps in BOLD metadata. by Frederik Stein (22146203)

“…ASAP was found to be superior to RESL due to RESL’s adherence to the concept of the DNA barcoding gap. Moreover, we found that taxonomic misassignments, inconsistencies in BIN formation, and missing metadata also contribute significantly to unreliable identifications. …”

Increasing gaps and decreasing returns attenuate spending effects. by William Minozzi (8564712)

Results of the distance-based significance tests of class attribution. by Felix Riede (7113146)

Most significant annotation class for benchmark vs. other genes. by Corbin Quick (9363574)

“…<p>Most significant single-annotation test (x-axis) for genes with one or more gene-based p-value ≤ 5e-6. …”

Range of significant wave height for each class. by Ji-Woo Kwon (17304933)

Class status with most significant 11 input features. by Umme Marzia Haque (11846815)

Classification results based on three levels of experiments, binary classification, multi-class classification with 3-class and 4-class. by Saima Farhan (22127216)

Latent class significance of group membership by participant characteristic. by Jennifer Donnan (16951558)

Gap junction (GJ) communication decreases the proportion of cells exhibiting Ca²⁺ spikes. by Dharsan K. Soundarrajan (11632145)

Final class counts and proportions for latent classes based on distributed probabilities. by Okikiolu Badejo (18404458)

HLA class I and class II alleles with study-wide significance for association with leprosy. by Monica Dallmann-Sauer (8856518)

T-test comparison between groups based on “class”. by Veerle Van Hoeck (209130)

Proportions of participants in each latent class based on the 4-class LCA model. by Leo Lundy (18522264)

Subjects:

Distribution of SNPs and their frequencies based on mutation classes. by Sadia Afrin Runa (22504971)

Distribution of digital financial inclusion impact on carbon intensity gap in agriculture by province. by Lingzhi Tan (19146572)

Fungal classes significantly differ from each other with respect to MOTU RNA:DNA read ratios. by Martino Adamo (9927999)

Top 1% significant features of GDZY dataset. by Jun Tan (46388)

Spatial heterogeneity in the impact of digital financial inclusion on the carbon reduction gap in agricultural regions. by Lingzhi Tan (19146572)

The KEGG results of significantly up-regulated and down-regulated genes. by Wentao Cai (4221916)

Subjects:

The relative duration and distance in each time gap. by Tomohiro Gonjo (8825780)