GLS inhibition decreases IL-1β secretion <i>in vitro</i>. by Bárbara Ponzilacqua-Silva (17002156)

Task 2 one-way ANCOVA significant results. by Mucahit Gemici (21519313)

Task 1 two-way ANCOVA significant results. by Mucahit Gemici (21519313)

Significant repeated measurements sEMG outcomes. by María Benito-de-Pedro (22057468)

“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”

Significant single measurement sEMG outcomes. by María Benito-de-Pedro (22057468)

“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”

Table 6 - Gain and loss: Human and environmental wellbeing – drivers of Kilimanjaro’s decreasing biodiversity by Andreas Hemp (730415)

GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

Significant clusters: Coronal PET images showing brain regions with significant (p < 0.001 and K > 50) metabolic inhibition (A-G) and activation (H-I) in rats following cocaine sel... by Christopher Rowan (21499924)

Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. by Søren Egstrand (10906087)

“…All groups were compared by Kruskal Wallis test with <i>post hoc</i> test after Dunn with Bonferroni adjustment showing significant decreased Ki-67 labeling index of <i>Cina1</i> compared to <i>Cina2</i> (p = 0.006) and the untreated CKD groups (p = 0.0001 and p = 0.0002, respectively). …”

Table 2 - by Rosanna Mary Rooney (17595801)

“…Despite a global decrease over the last 30 years, youth crime remains prevalent. …”

RTA408 significantly reduces RGCs loss. by Hongmei Qian (538647)

DALY and HLY in Portugal, 1990–2019. The first graph shows a decreasing trend of DALY and the second graph shows an increasing trend of HLY. by Aida Isabel Tavares (12080156)

Preference for the EIA – conjoint results. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Marginal means – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample attribute table. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Subgroup analysis – Political affiliation. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Sample scenario description. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

AMCEs – Pooled across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Methodological flowchart. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”

Preference for the EIA vs. ETA across scenarios. by Mehdi Mourali (10170245)

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”