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ASIC Upgrade Daily Contribution Change — Weighted Result Mean
x402
ASIC Upgrade Daily Contribution Change — Weighted Result Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes a weighted mean of daily net contribution change (revenue gain + energy savings minus overhead) across multiple ASIC upgrade scenarios using caller-supplied weights.
Price / call$0.01
Success—
StatusUnknown
How this service works
ASIC upgrade daily contribution change — Weighted result mean: Weighted result mean for ASIC upgrade daily contribution change. Supplied mining assumptions only; formula and units disclosed. No live prices, mining or guaranteed return. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one bounded weighted result mean report.
Output
Returns a single weighted result mean value representing the average net daily contribution change (extra_revenue_usd + saved_energy_usd - extra_overhead_usd) across all input rows, weighted by the provided weights array. Output is a bounded USD figure with formula and units disclosed; no live prices or guaranteed returns are implied.
Example use cases
Hardware refresh planning across farm tiers
“I'm evaluating four different ASIC upgrade tiers for my mining farm. Tier A daily figures: $5 extra revenue, $3 energy savings, $1.50 overhead; Tier B: $6, $3.50, $2; Tier C: $4.50, $2.80, $1.20; Tier D: $7, $4, $2.50 — weight them 1, 3, 2, 4 since Tier B and D are more likely. What's the weighted mean net daily contribution change?”
Seasonal profitability scenario aggregation
“I have six seasonal ASIC upgrade scenarios modeled for summer operations. Each has different energy savings, extra revenue, and overhead figures. Can you compute the weighted mean daily contribution change if I assign higher weights to the peak-heat months where energy savings are biggest? Rows: [{saved_energy_usd:4,extra_revenue_usd:5,extra_overhead_usd:1.5},{saved_energy_usd:5,extra_revenue_usd:6,extra_overhead_usd:2},{saved_energy_usd:3,extra_revenue_usd:4,extra_overhead_usd:1},{saved_energy_usd:5.5,extra_revenue_usd:6.5,extra_overhead_usd:2.2},{saved_energy_usd:4.5,extra_revenue_usd:5.5,extra_overhead_usd:1.8},{saved_energy_usd:3.5,extra_revenue_usd:4.5,extra_overhead_usd:1.2}], weights: [1,2,1,3,2,1].”
Comparing two candidate ASIC models with confidence weights
“I'm comparing two ASIC upgrade candidates. Model X daily: $2.80 extra revenue, $1.90 energy savings, $0.80 overhead — I'm 70% confident in this scenario. Model Y daily: $3.50 extra revenue, $2.20 energy savings, $1.10 overhead — 30% confidence. Can you give me the probability-weighted mean daily contribution change using weights 7 and 3?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-mining-upgrade-benefit-weighted-mean?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a single aggregated weighted mean across multiple ASIC upgrade daily contribution scenarios — particularly when scenarios have unequal probability or importance and you want one summary metric. Prefer this over a batch calculation endpoint when the goal is a single weighted summary rather than per-row outputs, and over a simple mean when scenarios must be weighted differently.
Side effects
- Mismatched array lengths between rows and weights returns a validation error
- Fewer than 2 rows or weights causes a minItems constraint failure
- Negative extra_overhead_usd values rejected (minimum is 0)
- Values exceeding maximum bounds (1e16) will fail schema validation
- Non-numeric inputs in rows or weights produce type errors
- Payment failure or insufficient USDC balance returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| weights | array |
Tags
x402
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