C.C. Palliser

477 total citations
18 papers, 394 citations indexed

About

C.C. Palliser is a scholar working on Agronomy and Crop Science, Molecular Biology and Environmental Chemistry. According to data from OpenAlex, C.C. Palliser has authored 18 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Agronomy and Crop Science, 3 papers in Molecular Biology and 3 papers in Environmental Chemistry. Recurrent topics in C.C. Palliser's work include Ruminant Nutrition and Digestive Physiology (6 papers), Genetic and phenotypic traits in livestock (3 papers) and Reproductive Physiology in Livestock (3 papers). C.C. Palliser is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (6 papers), Genetic and phenotypic traits in livestock (3 papers) and Reproductive Physiology in Livestock (3 papers). C.C. Palliser collaborates with scholars based in New Zealand, United States and United Kingdom. C.C. Palliser's co-authors include Robert McKibbin, David Parry, M.D. Hanigan, Pablo Gregorini, Meryl E. Wastney, B.S. Thorrold, Pierre Beukes, K.A. Macdonald, J.A.S. Lancaster and G. Levy and has published in prestigious journals such as Journal of Dairy Science, Journal of Environmental Management and Proteins Structure Function and Bioinformatics.

In The Last Decade

C.C. Palliser

18 papers receiving 381 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
C.C. Palliser New Zealand 10 118 95 74 68 66 18 394
I. A. Watson Australia 13 83 0.7× 26 0.3× 37 0.5× 13 0.2× 36 0.5× 38 663
R. J. Gummerson United States 6 54 0.5× 33 0.3× 62 0.8× 29 0.4× 2 0.0× 6 821
K. Fukuyama Japan 12 85 0.7× 44 0.5× 6 0.1× 37 0.5× 23 0.3× 37 478
Nimrod Schwartz Israel 14 39 0.3× 10 0.1× 118 1.6× 12 0.2× 29 0.4× 28 478
Haichao Guo China 13 59 0.5× 7 0.1× 16 0.2× 38 0.6× 14 0.2× 38 531
Defeng Zhu China 11 20 0.2× 16 0.2× 28 0.4× 4 0.1× 65 1.0× 15 451
Dean M Peterson Hungary 6 8 0.1× 48 0.5× 23 0.3× 220 3.2× 17 0.3× 11 452
Helen Downie United Kingdom 9 13 0.1× 11 0.1× 59 0.8× 54 0.8× 27 0.4× 11 434

Countries citing papers authored by C.C. Palliser

Since Specialization
Citations

This map shows the geographic impact of C.C. Palliser's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by C.C. Palliser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C.C. Palliser more than expected).

Fields of papers citing papers by C.C. Palliser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C.C. Palliser. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by C.C. Palliser. The network helps show where C.C. Palliser may publish in the future.

Co-authorship network of co-authors of C.C. Palliser

This figure shows the co-authorship network connecting the top 25 collaborators of C.C. Palliser. A scholar is included among the top collaborators of C.C. Palliser based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with C.C. Palliser. C.C. Palliser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Rutherford, J. Christopher, et al.. (2018). Eutrophication In Lake Rotorua. 2. Using ROTAN and OVERSEER to model historic, present and future nitrogen loads. New Zealand Journal of Marine and Freshwater Research. 53(1). 128–161. 3 indexed citations
2.
Palliser, C.C., et al.. (2018). Eutrophication in Lake Rotorua. 1. Using OVERSEER to estimate historic nitrogen loads. New Zealand Journal of Agricultural Research. 62(1). 112–129. 3 indexed citations
3.
Cox, Trevor J., et al.. (2013). An integrated model for simulating nitrogen trading in an agricultural catchment with complex hydrogeology. Journal of Environmental Management. 127. 268–277. 16 indexed citations
4.
McBride, Graham B., et al.. (2012). Estimating health risks to water users: Marrying hydrodynamic models and risk models. Water Practice & Technology. 7(4). 8 indexed citations
5.
Hanigan, M.D., C.C. Palliser, & Pablo Gregorini. (2009). Altering the representation of hormones and adding consideration of gestational metabolism in a metabolic cow model reduced prediction errors. Journal of Dairy Science. 92(10). 5043–5056. 42 indexed citations
6.
Beukes, Pierre, C.C. Palliser, K.A. Macdonald, et al.. (2008). Evaluation of a Whole-Farm Model for Pasture-Based Dairy Systems. Journal of Dairy Science. 91(6). 2353–2360. 72 indexed citations
7.
Hanigan, M.D., A.G. Ríus, E.S. Kolver, & C.C. Palliser. (2007). A Redefinition of the Representation of Mammary Cells and Enzyme Activities in a Lactating Dairy Cow Model. Journal of Dairy Science. 90(8). 3816–3830. 20 indexed citations
8.
Wastney, Meryl E., G. Levy, WJ Fulkerson, et al.. (2005). Applying differential evolution to a whole-farm model to assist optimal strategic decision making. Lincoln University Research Archive (Lincoln University). 2 indexed citations
9.
Beukes, Pierre, et al.. (2005). Comparing risk for different dairy farm management systems in Taranaki using the Dexcel Whole Farm Model. Proceedings of the New Zealand Grassland Association. 103–107. 6 indexed citations
10.
Beukes, Pierre, B.S. Thorrold, Meryl E. Wastney, et al.. (2005). Modelling the bi-peak lactation curves of summer calvers in New Zealand dairy farm systems. Australian Journal of Experimental Agriculture. 45(6). 643–643. 15 indexed citations
11.
Macdonald, K.A., et al.. (2002). Effect of frequency of pasture measurement on estimation of pasture growth rates: field observations and predictions of a whole farm model. Proceedings of the New Zealand Grassland Association. 91–95. 2 indexed citations
12.
Smith, Thomasin A., Paul D. Hempstead, C.C. Palliser, & David Parry. (2002). Modeling α‐helical coiled‐coil interactions: The axial and azimuthal alignment of 1B segments from vimentin intermediate filaments. Proteins Structure Function and Bioinformatics. 50(2). 207–212. 9 indexed citations
13.
Palliser, C.C. & S.L. Woodward. (2002). Using Models to Predict Methane Reduction in Pasture- Fed Dairy Cows. ScholarsArchive (Brigham Young University). 7 indexed citations
14.
Palliser, C.C. & David Parry. (2000). Quantitative comparison of the ability of hydropathy scales to recognize surface ?-strands in proteins. Proteins Structure Function and Bioinformatics. 42(2). 243–255. 50 indexed citations
15.
Palliser, C.C., Malcolm W. MacArthur, & David Parry. (2000). Surface β-Strands in Proteins: Identification Using an Hydropathy Technique. Journal of Structural Biology. 132(1). 63–71. 5 indexed citations
16.
Palliser, C.C. & Robert McKibbin. (1998). A Model for Deep Geothermal Brines, II: Thermodynamic Properties – Density. Transport in Porous Media. 33(1-2). 129–154. 36 indexed citations
17.
Palliser, C.C. & Robert McKibbin. (1998). A Model for Deep Geothermal Brines, I: T-p-X State-Space Description. Transport in Porous Media. 33(1-2). 65–80. 41 indexed citations
18.
Palliser, C.C. & Robert McKibbin. (1998). A Model for Deep Geothermal Brines,III: Thermodynamic Properties – Enthalpy and Viscosity. Transport in Porous Media. 33(1-2). 155–171. 57 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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