{
  "name": "Radio Source Classification Tree",
  "description": "A decision tree for classifying radio sources based on physical diagnostics and multi-Gaussian fitting.",
  "version": "2.0-GaussianFit",
  "parameters": {
    "SNR": "Signal-to-Noise Ratio (Peak Flux / Error)",
    "DC_Maj_arcsec": "Major axis of detected component in arcseconds",
    "BMAJ_arcsec": "Beam major axis in arcseconds",
    "Dist_Peak_Core": "Euclidean distance between the brightest pixel and the geometric center (pixels)",
    "Diag_Radius": "Threshold for peak offset diagnosis (0.5 * Beam in pixels)",
    "Flux_Ratio": "Ratio of the brightest residual (after excising 2.0*Beam core) to the original peak flux",
    "Best_N": "The number of Gaussian components (1, 2, or 3) in the best-fit model selected by BIC"
  },
  "decision_tree": [
    {
      "step": 1,
      "condition": "SNR < 5.0",
      "description": "Signal Quality Check",
      "if_true": "Classification: 噪声 (Noise)",
      "if_false": "Go to step 2"
    },
    {
      "step": 2,
      "condition": "DC_Maj_arcsec <= 1.5 * BMAJ_arcsec",
      "description": "Morphological Compactness Check",
      "if_true": "Classification: 致密源 (Compact)",
      "if_false": "Go to step 3"
    },
    {
      "step": 3,
      "condition": "Dist_Peak_Core > Diag_Radius (0.5 * Beam)",
      "description": "Peak Location Diagnosis (Physical Center vs. Hotspot)",
      "if_true": "Go to step 4 (Branch A: Peak Outside / FR II Family)",
      "if_false": "Go to step 5 (Branch B: Peak Inside / FR I Family)"
    },
    {
      "step": 4,
      "condition": "Best_N == 3",
      "description": "Branch A (FR II Family): Check Best_N from Fitting",
      "if_true": "Classification: FR II (Triple)",
      "if_false": "Classification: FR II (Double)"
    },
    {
      "step": 5,
      "condition": "Flux_Ratio < 0.3",
      "description": "Branch B (FR I Family): Check core excision residual (Compactness)",
      "if_true": "Classification: FR I (Compact)",
      "if_false": "Go to step 6"
    },
    {
      "step": 6,
      "condition": "Flux_Ratio > 0.5",
      "description": "Branch B (FR I Family): Check core excision residual (Structure Strength)",
      "if_true": "Go to step 7 (High Residual Structure)",
      "if_false": "Go to step 8 (Marginal Structure)"
    },
    {
      "step": 7,
      "condition": "Best_N == 2",
      "description": "Branch B - High Residual: Check for Core-Jet morphology",
      "if_true": "Classification: FR I (Core-Jet)",
      "if_false": "Go to step 9"
    },
    {
      "step": 8,
      "condition": "Best_N == 1",
      "description": "Branch B - Marginal Residual: Check for Resolution",
      "if_true": "Classification: FR I (Compact)",
      "if_false": "Classification: FR I (Resolved)"
    },
    {
      "step": 9,
      "condition": "Best_N == 3",
      "description": "Branch B - High Residual: Check for Complex morphology",
      "if_true": "Classification: FR I (Complex)",
      "if_false": "Classification: FR I (Extended Blob)"
    }
  ],
  "classification_mapping": {
    "噪声 (Noise)": "信噪比不足，无法确认源结构",
    "致密源 (Compact)": "尺寸极小，未被波束分辨的点源",
    "FR II (Triple)": "边缘增亮，且模型识别出核心与双瓣共存 (N=3)",
    "FR II (Double)": "边缘增亮，核心不可见或极暗，仅识别出双瓣结构",
    "FR I (Core-Jet)": "核心主导，挖核后残留显著，模型拟合为双组件 (核心+喷流)",
    "FR I (Complex)": "核心主导，挖核后残留显著，模型拟合为三组件 (核心+晕/复杂结构)",
    "FR I (Resolved)": "核心主导，中等残留比，模型认为多组件拟合优于单组件 (边缘可分辨)",
    "FR I (Compact)": "核心主导，挖核后几乎无残留，或模型偏向单高斯 (本质致密)"
  },
  "references": [
    {
      "id": "ref1",
      "citation": "Fanaroff, B. L., & Riley, J. M. 1974, MNRAS, 167, 31P",
      "description": "Original definition of the Fanaroff-Riley (FR) classification, distinguishing FR I and FR II radio galaxies based on the relative position of high-brightness regions."
    },
    {
      "id": "ref2",
      "citation": "Best, P. N., & Heckman, T. M. 2012, MNRAS, 421, 1569",
      "description": "Investigates the fundamental dichotomy in the radio-AGN population (HERG vs. LERG), linking radio source evolution to accretion modes and host galaxy properties."
    },
    {
      "id": "ref3",
      "citation": "Hancock, P. J., Murphy, T., Gaensler, B. M., Hopkins, A., & Curran, J. R. 2012, MNRAS, 422, 1812",
      "description": "Introduces AEGEAN for radio surveys: uses a curvature map to detect component peaks and perform constrained multi-elliptical-Gaussian fitting of islands, improving characterization of blended/multi-component sources."
    },
    {
      "id": "ref4",
      "citation": "Mingo, B., et al. 2019, MNRAS, 488, 2701",
      "description": "Revisits the Fanaroff-Riley dichotomy using the LOFAR Two-Metre Sky Survey (LoTSS), analyzing morphological parameters like the Concentration Index to classify complex sources."
    }]
}