Metodologi Skor Penyedia FTSO

if (rate <= 0 || medianRate <= 0): score = 0
else:
  ratio = rate / medianRate
  score = min(25, round(ratio * 12.5 * 10) / 10)   // 1 decimal place

// Anomaly detection: providers > 3× the median are capped at
// median × 3 for scoring purposes (prevents data outliers from
// distorting the linear curve).

if (fseAccuracySecondary > 0):
  pct = fseAccuracySecondary / 100
  if (pct >= 97) score = 25
  elif (pct >= 95) score = 18 + (pct - 95) * 3.5     // 95 → 18,  97 → 25
  elif (pct >= 93) score = 16 + (pct - 93) * 1       // 93 → 16,  95 → 18
  elif (pct >= 90) score = 13 + (pct - 90) * 1       // 90 → 13,  93 → 16
  elif (pct >= 85) score = 10 + (pct - 85) * 0.6     // 85 → 10,  90 → 13
  elif (pct >= 80) score = 6  + (pct - 80) * 0.8     // 80 → 6,   85 → 10
  else              score = max(0, 2 + (pct - 70) * 0.4)
elif (fseAccuracyPrimary > 0):
  // Primary fallback: similar piecewise linear curve.
else:
  score = WEIGHT_ACCURACY / 2   // Neutral — no FSE data

earned = last 12 epochs where rewardRate > 0, keyed by epochId
pairs  = [earned[i-1], earned[i]] where epochId[i] - epochId[i-1] == 1
if (pairs.length < 3) return 10        // Neutral — too few consecutive pairs

// DOWNSIDE volatility only: rises never hurt, so a stable or RISING
// rate scores near full and a recovery lifts the score. Only drops
// between CONSECUTIVE epochs count, in proportion to depth (RMS),
// weighted toward recent pairs so an active recovery pulls the score up.
drops[i] = max(0, (prev - cur) / prev)     // rise -> 0
w[i]     = 0.8 ^ (age of pair)             // newest pair = highest
cv       = sqrt( sum(w[i] * drops[i]^2) / sum(w[i]) )
score    = max(0, round((1 - min(1, cv * 6)) * 20 * 10) / 10)

if (!isActive) score = 0     // see "Active" below
else:
  score = 3   // active baseline
  if (hasSubmitAddress AND hasSigningPolicyAddress AND voterRegistered):
    score += 4   // V1 registered
  if (fseFtsoScaling)  score += 8/3   // ~2.67 each
  if (fseFastUpdates)  score += 8/3
  if (fseFdc)          score += 8/3
  score = min(15, round(score * 10) / 10)

anchor = max(lowest active fee observed, protocol fee floor)
// FIP-16 sets a 20% minimum entity fee. All 98 providers charge
// exactly 20%, so the anchor is 20% and nobody is docked for
// charging the only fee the protocol permits. Same curve and
// same anchor the validator page's Fee dimension uses.

if (!isActive) score = 0
d = fee - anchor              // distance ABOVE the best real offer
if (d <= 0)  score = 15       // at or below the anchor → full marks
elif (d <= 5)  score = 15 - d * 0.43
elif (d <= 10) score = 12.9 - (d - 5) * 0.64
elif (d <= 15) score = 9.6 - (d - 10) * 0.86
elif (d <= 20) score = 5.4 - (d - 15) * 1.07
else: score = 0               // extractive

if (no fseNodeIDs) score = 0
if (mirrorStatsMap empty) score = 12 / 2 = 6   // Neutral seed before data lands

activeCount = nodes_with_status_active
fraction = activeCount / fseNodeIDs.length
base = 12 * fraction

// Overperformance bonus per node, applied only when ALL gates pass:
//   - >= 30 days observed since first reading (firstObservedAtMs)
//   - >= 3 paid stake observations
//   - finite medianOverpaymentRatio
// Bayesian shrinkage with prior k=5 toward 1.0 (neutral):
//   shrunken = (observedRatio * N + 1.0 * 5) / (N + 5)
// Bucketed bonus from shrunken:
//   < 1.05 → 0    < 1.15 → 1    < 1.30 → 2    >= 1.30 → 3

avgBonus = sum_per_node(bonus) / fseNodeIDs.length
score = round((base + avgBonus) * 10) / 10

if (count <= 5)   score = 0
elif (count >= 500) score = 12
else:
  ratio = log(count / 5) / log(100)   // maps [5, 500] → [0, 1]
  score = round(min(12, max(0, ratio * 12)) * 10) / 10

if (fseActive) score = 10
elif (rewardRate > 0) score = 7
else score = 0

change = abs(votePowerDailyChangePct * 100)
if (change < 1)  score = 10
elif (change < 3) score = 10 - (change - 1) * 1.5     // 1 → 10, 3 → 7
elif (change < 5) score = 7  - (change - 3) * 1.5     // 3 → 7,  5 → 4
elif (change < 10) score = 4 - (change - 5) * 0.4     // 5 → 4, 10 → 2
else               score = max(0, 2 - (change - 10) * 0.1)

if (no fspData OR totalEpochs <= 0) score = 5

// active window = epochs from the provider's first paid epoch to now
missed = (active-window epochs) - (epochs the provider was paid)
score = max(0, 10 - missed * 3)

if (no name) score = 0
elif (name starts with 0x or matches hex regex) score = 0
elif (name.length < 4) score = 4
else score = 8

ownBond      = operator's own P-Chain node bond (FLR)
total        = ownBond + delegated WFLR vote power
alignment    = piecewise-linear ratio curve (0% → 0 … ≥10% → 7)
absolute     = min(7, ownBond / 5,000,000 * 7)   // saturates at 5M FLR
score        = max(alignment, absolute)