Keep an unknown character state distinct from observed absence
Incomplete specimens and uncertain sequence alignment can leave a character unobserved. Coding an unknown as absence invents a biological observation. Uncertainty should be retained in the matrix and propagated to the inference rather than resolved in whichever direction supports a favored tree.
Learning outcome: Compare unknown, forced0 and observed1 while keeping one1100 column. Reconstruct the score change and report every shortest split. State which additional actual observation would distinguish missing information from an observed absence.
Starting recap
Reconstruct character-based relationships, preserve topological and sampling uncertainty, and distinguish lineage, species and detection measures of diversity.
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Try
With1?00, one1010 conflict and one1100 column, AB|CD scores1+2+1=4 and AC|BD scores1+1+2=4; AD|BC scores1+2+2=5. Observing B=1 changes the first column to1100 and gives totals4,5,6, favoring AB|CD.
Open the experimentPredict
Does allowing a missing state to take the minimum-cost value establish that it actually had that value?
Experiment
Compare unknown, forced0 and observed1 while keeping one1100 column. Reconstruct the score change and report every shortest split. State which additional actual observation would distinguish missing information from an observed absence.
Compare ambiguous state handling with forced absence
Worked teaching model · synthetic values · Missing state? allows{0,1} during minimization; it is not coded as observed0. Original character1?00 plus selected1100 columns and one1010 conflict. Conditional minimum-change scores do not provide a probability that a missing state is1.
Reset keeps your prediction, captures and practice history.
Unknown does not mean absent: preserve ambiguity instead of manufacturing an observed state.
Allowing both states may lower a score or leave several equally short trees. This is optimization over uncertainty, not evidence that the unobserved state took whichever value favors a preferred tree. Report ties and obtain independent data.
Taxa A B C D; columns: 1?00 ; 1010 ; 1100
| Quantity | Value | Unit |
|---|---|---|
| AB|CD minimum total changes | 4 | changes |
| AC|BD minimum total changes | 4 | changes |
| AD|BC minimum total changes | 5 | changes |
Retain prior predictions, settings and quantities in the notebook. These are original supplied/calculated comparisons, not physical specimen observations or laboratory participation.
Unknown does not mean absent: preserve ambiguity instead of manufacturing an observed state.
Allowing both states may lower a score or leave several equally short trees. This is optimization over uncertainty, not evidence that the unobserved state took whichever value favors a preferred tree. Report ties and obtain independent data.
Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.
Understand
Apply
Public practice checks a specific claim. It does not establish independent mastery.
Use unknown1?00 with1010 but no additional1100 column. Which split is shortest?
Continue
Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.
Skipping retains experiments and awards no mastery.
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