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A maximum entropy and multinomial logistic regression modeling framework was applied to presence-background data to predict most likely habitat type at a spatial resolution of 10 m.", "geometryType": "esriGeometryPolygon", "sourceSpatialReference": { "wkid": 104145, "latestWkid": 6318, "xyTolerance": 8.983152841195215E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 1.111948722222222E9, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 }, "copyrightText": "Sterne TK, Retchless D, Allee R, Highfield W. 2020. Predictive modelling of mesophotic habitats in the north-western Gulf of Mexico. Aquatic Conserv.: Mar. Freshw. 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