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diff --git a/src/de/lmu/ifi/dbs/elki/result/outlier/ProbabilisticOutlierScore.java b/src/de/lmu/ifi/dbs/elki/result/outlier/ProbabilisticOutlierScore.java
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+package de.lmu.ifi.dbs.elki.result.outlier;
+/*
+This file is part of ELKI:
+Environment for Developing KDD-Applications Supported by Index-Structures
+
+Copyright (C) 2011
+Ludwig-Maximilians-Universität München
+Lehr- und Forschungseinheit für Datenbanksysteme
+ELKI Development Team
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Affero General Public License for more details.
+
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see <http://www.gnu.org/licenses/>.
+*/
+
+/**
+ * Outlier score that is a probability value in the range 0.0 - 1.0
+ * 
+ * But the baseline may be different from 0.0!
+ * 
+ * @author Erich Schubert
+ */
+public class ProbabilisticOutlierScore implements OutlierScoreMeta {
+  /**
+   * Actual minimum seen, if given by the algorithm.
+   */
+  private double actualMinimum = Double.NaN;
+  /**
+   * Actual maximum seen, if given by the algorithm.
+   */
+  private double actualMaximum = Double.NaN;
+  /**
+   * Theoretical baseline specified by the algorithm. Defaults to 0.0 in short constructor.
+   */
+  private double theoreticalBaseline = Double.NaN;
+
+  /**
+   * Default constructor. No actual values, Baseline 0.0
+   */
+  public ProbabilisticOutlierScore() {
+    this(Double.NaN, Double.NaN, 0.0);
+  }
+
+  /**
+   * Constructor with baseline only.
+   * 
+   * @param theoreticalBaseline Baseline
+   */
+  public ProbabilisticOutlierScore(double theoreticalBaseline) {
+    this(Double.NaN, Double.NaN, theoreticalBaseline);
+  }
+
+  /**
+   * Constructor with actual values, and a baseline of 0.0
+   * 
+   * @param actualMinimum actual minimum seen
+   * @param actualMaximum actual maximum seen
+   */
+  public ProbabilisticOutlierScore(double actualMinimum, double actualMaximum) {
+    this(actualMinimum, actualMaximum, 0.0);
+  }
+
+  /**
+   * Full constructor.
+   * 
+   * @param actualMinimum actual minimum seen
+   * @param actualMaximum actual maximum seen
+   * @param theoreticalBaseline theoretical baseline
+   */
+  public ProbabilisticOutlierScore(double actualMinimum, double actualMaximum, double theoreticalBaseline) {
+    super();
+    this.actualMinimum = actualMinimum;
+    this.actualMaximum = actualMaximum;
+    this.theoreticalBaseline = theoreticalBaseline;
+  }
+
+  @Override
+  public double getActualMinimum() {
+    return actualMinimum;
+  }
+
+  @Override
+  public double getActualMaximum() {
+    return actualMaximum;
+  }
+
+  @Override
+  public double getTheoreticalBaseline() {
+    return theoreticalBaseline;
+  }
+
+  @Override
+  public double getTheoreticalMaximum() {
+    return 1.0;
+  }
+
+  @Override
+  public double getTheoreticalMinimum() {
+    return 0.0;
+  }
+
+  @Override
+  public double normalizeScore(double value) {
+    return value;
+  }
+
+  @Override
+  public String getLongName() {
+    return "Outlier Score Metadata";
+  }
+
+  @Override
+  public String getShortName() {
+    return "outlier-score-meta";
+  }
+}
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