Description
Return weight×ln(ratio)/ln(base).
Evidence weights and credences are numerical representations under a chosen model. Likelihood ratios, probabilities, logarithmic weights and confidence bounds have different meanings; one local calculation does not establish the truth of a claim.
Return weight×ln(ratio)/ln(base).
When to use this tool
Use Evidence Logweight Term when you need an explicit evidence-weight or probability-consistency term.
How to use the tool and how it works
- Enter likelihoodRatio, weight, logBase. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read logWeight. Use the output convention below.
Require positive likelihood ratio, nonnegative weight and positive logBase different from one. Return weight×ln(ratio)/ln(base).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| likelihoodRatio | Likelihood Ratio | Required. Finite number; strictly above 0. |
| weight | Weight | Required. Finite number; minimum 0. |
| logBase | Positive base different from one; bases below one reverse the customary log-evidence sign. | Required. Finite number; strictly above 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| logWeight | Log Weight | Required. Finite number. |
{
"input": {
"likelihoodRatio": 4,
"weight": 0.5,
"logBase": 2
},
"output": {
"logWeight": 1
}
}Limitations and assumptions
- A base between zero and one reverses the usual log-evidence sign. The value is a weighted log term, not an automatically normalized posterior or validated dependence adjustment.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Evaluate source quality and the complete inference model. Check likelihood meaning, dependence, prior assumptions, normalization and uncertainty rather than substituting counts or weights for justified evidence.
References
Similar or alternative tools
- Likelihood Evidence Direction One Pair
Divide true/false likelihood and label supports, opposes or neutral by their ordering.
- Testimonial Source Dependence Discount Term
Multiply logEvidence by weight×count and return that fractional equivalent source count.