Effect of <i>slc43a3</i> deletion on physical activity of male and female WT and KO mice. by Aaron L. Sayler (19797446)

Error metric values i.e. MAPE and NMRE in JJA (main rainy season) rainfall between station data and CHIRPS data set before and after bias correction. by Asnake Adane (19935018)

Time-based splitting strategy and forecast horizons. by Thierry Jean (20691795)

This is the data set that we used to reach the conclusions drawn in the manuscript with related metadata and methods. by Farayi Kaseke (19560197)

Mean standard errors across time points for the outcome of social stigma. by Ana Beato (20489933)

Means with standard errors across time points for the outcome of social distance. by Ana Beato (20489933)

Means with standard errors across time points for the outcome of intergroup anxiety. by Ana Beato (20489933)

Parameter estimates of linear mixed effects models for juvenile <i>M</i>. <i>mercenaria</i>, juvenile <i>M</i>. <i>arenaria</i> and juvenile <i>A</i>. <i>islandica</i> mean shell c... by Teagan McMahon (20108036)

Male flies with a mixed background have not responded to high temperature-mediated body fat loss. by Tucker Hopkins (20790529)

Means with standard errors across time points for the outcome of mental health knowledge. by Ana Beato (20489933)

Characteristics of HACE respondents by year. by David Henderson (4612354)

“…</p><p>Results</p><p>Overall patient satisfaction with general practice declined significantly over the 10 years, with mean positive scores dropping from 90.1% in 2011/12 to 70.5% in 2021/22. …”

related to Fig 3. (A) Live eggs induce AIM2 pyroptosome formation. Microscopy of AIM2-citrine macrophages stimulated with live eggs for 48 h. by Madhusoodhanan Suresh Kumar Meena Kumari (20896666)

Eggs jointly coordinate a caspase-1 and caspase-8 dependent pyroptotic cell death. by Madhusoodhanan Suresh Kumar Meena Kumari (20896666)

Impact of 5′ nucleotidase disruption on <i>M</i>. <i>bovis</i> growth phenotype in axenic conditions. by Aga E. Gelgie (17661720)

SHAP interpretation of the optimal machine learning model. by Wentao Yang (205781)

Structure diagram of ensemble model. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Fitting formula parameter table. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Test plan. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Fitting surface parameters. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Model generalisation validation error analysis. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”