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

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Pretreatment facial, intraoral photographs, and radiographs of the case with premolar tooth extraction. حسب Lijuan Liu (136685)

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

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Water footprint at regional levels in China. حسب Jianqin Ma (20328414)

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Characteristics of water footprint by sector at the regional level in China. حسب Jianqin Ma (20328414)

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The distribution of water footprint levels in China. a, 2005. b, 2010. c, 2015. d, 2022. حسب Jianqin Ma (20328414)

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Synergy and trade-offs of sectoral water use at the provincial level. حسب Jianqin Ma (20328414)

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Synergy and trade-offs of sectoral water use at the regional level in China. حسب Jianqin Ma (20328414)

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Decoupling index of water footprint and GDP at the regional level in China. حسب Jianqin Ma (20328414)

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Supporting information. حسب Jianqin Ma (20328414)

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Decoupling index of water footprint and GDP at the provincial level. حسب Jianqin Ma (20328414)

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Second-order partial correlation analysis of sectoral water use in China from 2005 to 2022. حسب Jianqin Ma (20328414)

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Characteristics of water footprint by sector at the provincial level. حسب Jianqin Ma (20328414)

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Preference for the EIA – conjoint results. حسب 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. حسب 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. حسب 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. حسب 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. حسب 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. حسب 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. حسب 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. …"