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Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs

机译：用于准确预测网站导航问题，非问题，问题严重性和维修有效性的工具

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Marilyn Hughes Blackmon; Muneo Kitajima; Peter G. Polson;
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年度 2005
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1. Academic health sciences library Website navigation: an analysis of forty-one Websites and their navigation tools [J] . Stewart M. Brower Bulletin of the Medical Library Association. . 2004,第4期

机译：学术健康科学图书馆网站导航：对41个网站及其导航工具的分析
2. Academic health sciences library Website navigation: an analysis of forty-one Websites and their navigation tools. [J] . Brower SM Journal of the Medical Library Association : . 2004,第4期

机译：学术健康科学图书馆网站导航：对41个网站及其导航工具的分析。
3. Are navigation systems accurate enough to predict the correction angle during high tibial osteotomy?: Comparison of navigation systems with 3-dimensional computed tomography and standing radiographs [J] . KyungB.S., KimJ.G., JangK.-M., American Journal of Sports Medicine . 2013,第10期

机译：导航系统是否足够准确以预测胫骨截骨术中的矫正角度？：将导航系统与3D计算机断层扫描和站立X线照片进行比较
4. Tool for Accurately Predicting Website Navigation Problems, Non-Problems, Problem Severity, and Effectiveness of Repairs [C] . Marilyn Hughes Blackmon, Muneo Kitajima, Peter G. Polson Conference on Human Factors in Computing Systems . 2005

机译：用于准确预测网站导航问题的工具，非问题，问题严重性和维修的有效性
5. Navigational characteristics effectiveness of pharmaceutical websites on consumer behaviour and pre-purchase intentions. [D] . Richard, Marie-Odile. 2003

机译：药品网站导航特性对消费者行为和购买前意图的有效性。
6. Academic health sciences library Website navigation: an analysis of forty-one Websites and their navigation tools [O] . Stewart M. Brower 2004

机译：学术健康科学图书馆网站导航：对41个网站及其导航工具的分析
7. Figure 3: Predicting abundances correctly (A)—Random Dataset and (B)—CAMI Dataset: Abundances predicted by different tools compared to the true abundance used for simulation. SLIMM predicted the abundances more accurately than the other tools. Kraken overestimates the abundance. GOTTCHA and mOTUs did not perform well in predicting the abundances. Violin plots (C)—Random Dataset and (D)—CAMI Dataset: SLIMM has the lowest divergence from true abundances. [O] . -1

机译：图3：正确预测丰度（a） - random dataSet和（b）-cami dataset：与用于模拟的真正丰度相比，不同工具预测的丰富。 Slimm比其他工具更准确地预测丰富。克朗高估了丰富的丰富。 Gottcha和Motus在预测丰富时没有表现良好。小提琴图（c）-random数据集和（d）-cami dataset：Slimm具有真正丰富的最低分歧。

Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs

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