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Barents Group LLC map of pearson correlation coefficients
Map of <t>Pearson</t> correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.
Map Of Pearson Correlation Coefficients, supplied by Barents Group LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/map of pearson correlation coefficients/product/Barents Group LLC
Average 90 stars, based on 1 article reviews
map of pearson correlation coefficients - by Bioz Stars, 2026-03
90/100 stars

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1) Product Images from "Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent"

Article Title: Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent

Journal: Nature Communications

doi: 10.1038/s41467-025-59992-9

Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.
Figure Legend Snippet: Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.

Techniques Used: Derivative Assay, Concentration Assay



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Image Search Results


Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.

Journal: Nature Communications

Article Title: Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent

doi: 10.1038/s41467-025-59992-9

Figure Lengend Snippet: Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.

Article Snippet: Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box.

Techniques: Derivative Assay, Concentration Assay

Diagram of the Pearson correlation coefficient matrix for input features.

Journal: ACS Omega

Article Title: Performance Prediction and Heating Parameter Optimization of Organic-Rich Shale In Situ Conversion Based on Numerical Simulation and Artificial Intelligence Algorithms

doi: 10.1021/acsomega.4c00323

Figure Lengend Snippet: Diagram of the Pearson correlation coefficient matrix for input features.

Article Snippet: Based on eq , the Pearson correlation coefficient matrix map between input factors was drawn using MATLAB, as shown in Figure .

Techniques: