D. Heslop

Molecular Biology · 2001–2017

A researcher in the Science corpus: 8 papers; trusts 12 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 49 citations into it; #2,419 of 17,773 by trust here, #10,193 by citations
• Geophysics — 39 citations into it; #222 of 1,958 by trust here, #629 by citations
• Atmospheric Science — 23 citations into it; #1,187 of 4,804 by trust here, #2,716 by citations
• Electronic, Optical and Magnetic Materials — 16 citations into it
• Biomedical Engineering — 9 citations into it
• Physiology — 8 citations into it

Whom D. Heslop trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. R. Egli
2. C. R. Pike
3. A. Roberts
4. M. Dekkers
5. D. Dunlop
6. Geoffrey J. McLachlan
7. Andrew J. Newell
8. A. Muxworthy
9. K. Verosub
10. RichardJ . Harrison

Who trusts D. Heslop overall

1. R. Egli
2. A. Roberts
3. Daniel P. Maxbauer
4. Joshua Feinberg
5. M. Dekkers
6. David L. Fox
7. G. McIntosh
8. Xiang Zhao
9. Liao Chang
10. Qingsong Liu

Papers from D. Heslop's perspective

Ordered by how strongly the researchers D. Heslop trusts endorse each paper. Same corpus, a different order for every researcher.

1. First‐order reversal curve diagrams: A new tool for characterizing the magnetic properties of natural samples
2. Quantification of magnetic coercivity components by the analysis of acquisition curves of isothermal remanent magnetisation
3. Analysis of isothermal remanent magnetization acquisition curves using the expectation-maximization algorithm
4. First order reversal curve diagrams and thermal relaxation effects in magnetic particles
5. Characterization of hematite (α-Fe2O3), goethite (α-FeOOH), greigite (Fe3S4), and pyrrhotite (Fe7S8) using first-order reversal curve diagrams
6. First-order reversal curve (FORC) diagrams for pseudo-single-domain magnetites at high temperature
7. Theory and application of the Day plot (Mrs/Ms versus Hcr/Hc) 1. Theoretical curves and tests using titanomagnetite data
8. Using time- and temperature-dependent Preisach models to investigate the limitations of modelling isothermal remanent magnetization acquisition curves with cumulative log Gaussian functions
9. Increasing the efficiency of paleointensity analyses by selection of samples using first-order reversal curve diagrams
10. Characterization of Individual Rock Magnetic Components by Analysis of Remanence Curves, 1. Unmixing Natural Sediments

Their papers

• Quantification of magnetic coercivity components by the analysis of acquisition curves of isothermal remanent magnetisation (2001) — 770 citations
• Analysis of isothermal remanent magnetization acquisition curves using the expectation-maximization algorithm (2002) — 278 citations
• Using time- and temperature-dependent Preisach models to investigate the limitations of modelling isothermal remanent magnetization acquisition curves with cumulative log Gaussian functions (2004) — 145 citations
• Searching for single domain magnetite in the “pseudo‐single‐domain” sedimentary haystack: Implications of biogenic magnetite preservation for sediment magnetism and relative paleointensity determinations (2012) — 183 citations
• Resolving the Origin of Pseudo‐Single Domain Magnetic Behavior (2017) — 199 citations
• Understanding fine magnetic particle systems through use of first‐order reversal curve diagrams (2014) — 392 citations
• A Critical Appraisal of the “Day” Diagram (2017) — 180 citations
• Prediction of Geochemical Composition from XRF Core Scanner Data: A New Multivariate Approach Including Automatic Selection of Calibration Samples and Quantification of Uncertainties (2015) — 210 citations