Dimethyl Sulfide Biosignature Claim Plausibility Rater

Bounded DMSclaim evidence checklist, not detect life or assign a calibrated claim probability. Independently witnessed columns in order: spectral feature independently replicated, retrieval/model degeneracy independently reviewed, systematic noise independently reviewed, nonbiological chemistry independently evaluated. Known missing and unknown evidence stay distinct; not approval, compliance, readiness, authenticity or safety certification.

Description

A DMS claim needs replicated spectral evidence and review of model and chemical alternatives.

A DMS claim needs replicated spectral evidence and review of model and chemical alternatives.^[1]

A checklist records scrutiny without assigning a calibrated plausibility rating. Use this tool to record known present, known missing and unknown checklist evidence.

When to use Dimethyl Sulfide Biosignature Claim Plausibility Rater

Use this tool to record known present, known missing and unknown checklist evidence. Establish the observation or experimental context, reference/calibration source, unit basis and adopted model assumptions.

How to use Dimethyl Sulfide Biosignature Claim Plausibility Rater and understand its results

Establish the observation or experimental context, reference/calibration source, unit basis and adopted model assumptions.
Enter observedCriterionFlags, criterionKnownFlags, using the field meanings and rules below, then run the tool.
Read result.witnessedCriteria, result.knownMissingCriteria, result.unknownCriteria. Interpret each field using the units, signs and evidence rules below.
If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.

Input field	Meaning	Value type	Requirement
observedCriterionFlags	Observed criterion flags; binary 0/1 in the order documented below	list of number	Required
criterionKnownFlags	Criterion known flags; 1 means known and 0 means unknown; keep the same item order	list of number	Required

Supply exactly 4 binary criterion flags and matched binary known flags in the listed order. Return witnessed labels where both flags are 1, known missing labels where known=1 and observed=0, and unknown labels wherever known=0, regardless of the placeholder observed flag. No overall diagnosis, pass or approval is inferred.

Zero-based column	Criterion
0	spectral feature independently replicated
1	retrieval/model degeneracy independently reviewed
2	systematic noise independently reviewed
3	nonbiological chemistry independently evaluated

witnessed={label_i:known_i=1 and observed_i=1}; missing={label_i:known_i=1 and observed_i=0}; unknown={label_i:known_i=0}

Apply the field units and exact ordering, boundary and evidence rules above.

Output field	Meaning	Value type
result	Structured result containing the calculation or selected reference fields below	object
result.witnessedCriteria	Criterion labels observed present with known evidence	list of string
result.knownMissingCriteria	Criterion labels known to be absent	list of values
result.unknownCriteria	Criterion labels whose evidence is unknown	list of values

json

{
  "input": {
    "observedCriterionFlags": [
      1,
      1,
      1,
      1
    ],
    "criterionKnownFlags": [
      1,
      1,
      1,
      1
    ]
  },
  "output": {
    "result": {
      "witnessedCriteria": [
        "spectral feature independently replicated",
        "retrieval/model degeneracy independently reviewed",
        "systematic noise independently reviewed",
        "nonbiological chemistry independently evaluated"
      ],
      "knownMissingCriteria": [],
      "unknownCriteria": []
    }
  }
}

Limitations and assumptions

Feature and criterion flags are independent annotations. Unknown evidence remains unknown; matching rules do not establish a diagnosis, cause, prediction or approval.

Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.

Alternative or Complementary methods

Use Phosphine Detection Significance Sigma Level Classifier to examine a related aspect: A fitted feature's sigma ratio divides amplitude by an independently established error.

Use Exoplanet Biosphere Detection Claim Confidence Composite Scorer where its separate inputs and scope apply: A biosphere claim requires observations, systematics review and examination of abiotic alternatives.

References

Dimethyl Sulfide Biosignature Claim Plausibility Rater — tool.io

Similar or alternative tools

Phosphine Detection Significance Sigma Level Classifier
A fitted feature's sigma ratio divides amplitude by an independently established error.
Exoplanet Biosphere Detection Claim Confidence Composite Scorer
A biosphere claim requires observations, systematics review and examination of abiotic alternatives.