The update step size of the attractor set in different regions. by Long Di (9977453)

Flow of premises through the study. by Eleni Mantzari (6991172)

Subjects:

Female regression coefficients for regression #3 across development in set size = 2 and set size = 4. by Juliana Chase (20469427)

“…All statistics are done identically and are reported in the text. There was a slight decrease in the regression coefficient weight of intercept for set size = 2 (A), but not set size = 4 (F). …”

Effect of session on winning model parameters for set size = 2 and set size = 4 for both male and females. by Juliana Chase (20469427)

“…<p>To test if mice adjusted one-back strategies with experience, we next compared how parameter weights (y-axis) changed across the 6 sessions analyzed for each mouse (x-axis). Since set size = 2 and set size = 4 days were interspersed, we combined set size data and analyzed sessions chronologically. …”

Data Set. by Yang Li (7082)

Parameter sets generated through Latin hypercube sampling. by Alexandra M. Campbell (3284094)

Strategy parameters across development for female mice in set size = 2 and set size = 4 from winning computational model. by Juliana Chase (20469427)

“…However, female mice had a significant decrease in parameter S1 “Inappropriate Lose-Shift” in set size = 4 (H: <i>p</i> = 0.04) with a trend in a similar direction in set size = 2 (C: <i>p</i> = 0.08).…”

Intraoperative facial and intraoral photographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Strategy parameters across development for male mice in set size = 2 and set size = 4 from winning computational model. by Juliana Chase (20469427)

“…RL parameter <i>α</i>₊ learning rate and decision noise parameter softmax <i>β</i> were stable across development in both set size = 2 (A-B) and set size = 4 (F-G). Both parameters S1 “Inappropriate Lose-Shift” and S3 “Inappropriate Lose-Stay” decreased significantly with age in set size = 2 (C: <i>p</i> = 0.02, E: <i>p</i> = 0.04), but not in set size = 4 (H,J). …”

Posttreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Pretreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Superimposition of the cephalometric tracings obtained before and after treatment of case with mandibular third molar extraction. by Lijuan Liu (136685)

Comparison of pretreatment cephalometric variables between premolar extraction and mandibular third molar extraction groups. by Lijuan Liu (136685)

Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively.... by Zoë Parker Cates (22184243)

“…The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively. …”

Fluctuation trend of the mean temperature index. by Chengyuan Hao (21615653)

“…Thirdly, the relevant e high temperature indices of plain urban area were larger while the relevant low temperature indices of mountain hilly area were smaller. …”

Variation curve of the mean temperature index. by Chengyuan Hao (21615653)

“…Thirdly, the relevant e high temperature indices of plain urban area were larger while the relevant low temperature indices of mountain hilly area were smaller. …”

Comparison of upper and lower arch crowding between premolar extraction group and the mandibular third molar extraction groups. by Lijuan Liu (136685)

Mean 0-30 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)

Mean 0-20 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)

Mean 0-10 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)