Stationary Phase Window Audit

Screen the final growth-curve window for a caller-defined relative stability band, rather than equating one count with carrying capacity.

Description

A stationary-looking final growth window has relatively little variation compared with its mean.

A stationary-looking final growth window has relatively little variation compared with its mean. Assessing a window separates observed stability from assuming one count represents a carrying capacity.^[1]

Screen the final growth-curve window for a caller-defined relative stability band, rather than equating one count with carrying capacity.

When to use Stationary Phase Window Audit

Use this tool to screen the final growth-curve window for a caller-defined relative stability band, rather than equating one count with carrying capacity.

Prepare the sample, count, growth or assay measurements requested by this tool. Confirm units, sampling periods and reporting bases; supply independently established comparison criteria where requested.

How to use Stationary Phase Window Audit and understand its results

Prepare the sample, count, growth or assay measurements requested by this tool. Confirm units, sampling periods and reporting bases; supply independently established comparison criteria where requested.
Enter observationHours, cellCounts, windowObservations, maximumRelativeRange using the field table and calculation rules, then run the tool.
Read windowMeanCellCount, relativeRange, stationaryWindow. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
observationHours	Observation hours	list of number	Required
cellCounts	Cell counts	list of number	Required
windowObservations	Window observations	integer; minimum: 2	Required
maximumRelativeRange	Maximum relative range	number; minimum: 0	Required

Enter aligned increasing observation hours and positive cell counts, an integer window size from 2 through the sample count, and nonnegative relative-range limit. The tool uses the final requested observations, calculates their mean and full range, and flags relativeRange at or below the limit. Times establish ordering but do not weight the mean.

Paired lists must be nonempty and have equal lengths. Sequences checked for increasing order must be nonempty and strictly increasing; additional calculation rules may require more samples.

relativeRange = (maximum−minimum)/windowMean

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
windowMeanCellCount	Window mean cell count	number
relativeRange	Relative range	number
stationaryWindow	Stationary window	boolean

json

{
  "input": {
    "observationHours": [
      0,
      1,
      2,
      3
    ],
    "cellCounts": [
      10,
      100,
      105,
      100
    ],
    "windowObservations": 3,
    "maximumRelativeRange": 0.1
  },
  "output": {
    "windowMeanCellCount": 101.66666666666667,
    "relativeRange": 0.04918032786885246,
    "stationaryWindow": true
  }
}

Limitations and assumptions

This is a supplied stability rule, not a growth-phase fit. Unequal sampling, measurement noise and an unsampled change can affect interpretation; a stable window does not establish carrying capacity.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.

Alternative or Complementary methods

Use Two Point Monod Parameters: Solve the exact two-point Monod model for mu-max and Ks, rejecting observations that imply nonpositive saturation parameters. For a complementary task, use Batch Biomass Productivity: Compute net biomass production and volumetric productivity in a constant-volume batch culture.

References

Stationary Phase Window Audit — tool.io

Similar or alternative tools

Two Point Monod Parameters
Solve the exact two-point Monod model for mu-max and Ks, rejecting observations that imply nonpositive saturation parameters.
Batch Biomass Productivity
Compute net biomass production and volumetric productivity in a constant-volume batch culture.