What a refusal does not say
Worth reading first: The survey this site cannot do · The sequence has a memory · A pattern with a rate.
An instrument that refuses is better than one that guesses. This site has said so four times and built the refusals to prove it: the angle recovery that declines because no divergence makes that pair the closest at that radius; the readout that returns nothing five times out of five at the rise where it would have been wrong; the fitter that has no solution when a parent is thinner than a branch it carries.
But a refusal is only a measurement if it says something about the specimen. And this one does not, because it has four causes.
The four
The two-comb readout declines when any of its tests fails, and the tests fail for different reasons.
The plant is too quiet. Below a disturbance of about 0.1 the sequence has too little variation to be a sample of anything, and in the model it locks onto the sampling grid. The cap on the correlation catches most of that, and what it catches it reports as a refusal.
The plant is too disturbed. Above about 0.5 the lattice is gone: divergences wander over the whole circle and the coherence test declines.
The shoot is too fast. A window of two hundred and fifty internodes spanning more than a rung has two combs in it at different spacings, neither of which wins by a sampling band, so the margin test declines.
Or the window was in the wrong place. Even on a slow shoot, a window that happens to straddle a transition has the same problem as a fast one.
Why that is worse than it sounds
A survey is a set of specimens, and what a survey does with a refusal decides what its numbers mean.
Suppose fifty stems are measured and thirty return a pair. The twenty that do not are either plants whose organs were not placed one at a time — which would be the result of the century — or plants that were quiet, or noisy, or growing quickly, or measured across a transition. A rate of refusal is not an estimate of anything unless the causes can be separated, and reporting “sixty per cent returned a pair” as though the other forty per cent were evidence about mechanism would be the worst possible use of the instrument.
That is the shape of the mixture problem this thread keeps failing to close, and it is worth naming precisely. It is not that the statistics are weak. Both are strong where they work: the comb is 0.64 against a band of 0.11, and the lag-one correlation is −0.6 against the same band. It is that the null has more than one cause, and no single sequence distinguishes them.
What a ruler removes
Two of the four are visible without the sequence at all.
The recorded scatter of the divergences — a mean and a standard deviation, which a ruler gives — is small at the quiet end and enormous at the loud one. In the model, the quiet end has a scatter under 0.4° and the loud end over a hundred degrees, and there is no ambiguity between them.
So the first line of the specification is: report the scatter alongside the readout. A refusal at 0.2° of scatter is a plant too quiet; at 40° it is a plant with no lattice; at 0.7° it is one of the other two.
That is not a subtle instrument and it is not free either — it needs the same azimuths measured to the same quarter of a degree — but it comes at no additional cost, because the sequence has already been recorded.
What a second window would remove
The third is separable too, and the method is one this site has used twice before.
The foundation phase caught a counting bug by counting in three bands of one head and requiring one answer. The expansion phase established that a cylinder’s pair is constant up the stem by counting in three disjoint bands and getting one answer — with the disc as the control, where three bands give three different pairs.
The same trick applies here. Read the window, then read a second window shifted by half its length. On a stem where the pair is not changing the two agree. On a stem where the window straddles a transition, or on a shoot too fast for a window to fit in a rung, they do not — because the two windows contain different mixtures of the two rungs.
That would separate “too fast or badly placed” from the other causes, and it would cost half as much stem again: three hundred and seventy-five internodes rather than two hundred and fifty.
It is specified rather than implemented, and the reason is worth being honest about: implementing it means deciding what “agree” means when one window refuses and the other does not, and that decision is not obvious. Two refusals could be one long stretch of unreadable stem or two different failures. Rather than write a rule and assert it, this is left as the next measurement.
The fourth, which is not separable
That leaves a window that fits inside a rung on a slow shoot, with a scatter in the working range, that still returns nothing.
There are two things that could be: the sequence has no comb because the organs were not placed one at a time in the presence of the ones already there, or the sequence has a comb too weak to clear at this length. And those are not separable by more of the same measurement, because the second is cured by a longer stem and the first is not — so a null at two hundred and fifty internodes has to be followed by a null at a thousand before it means anything at all.
Which puts a number on what the mechanism claim would cost. A positive result is two hundred and fifty internodes; a negative result is a thousand, and the asymmetry is the ordinary asymmetry of a null result, arriving here in a form that can be priced.
The specification, as it now stands
Every phase since the measurement phase has ended by restating what a survey would have to be, and each time the specification has got longer and more specific. Here it is with the two lines this phase adds:
- 250 consecutive internodes on an unbranched stem, azimuths to a quarter of a degree per organ. Half a degree costs sixty per cent more stem; one degree does not work at all.
- A shoot slower than 250 nodes per rung, or an established stem whose parastichy pair does not change across the window — checkable by counting the spirals at both ends of the window.
- Report the recorded scatter with every readout, refusal or not, so that two of the four causes of a null are separable.
- Two overlapping windows where the stem allows, so that a third is.
- And report attempted and returned, not returned alone.
The last line is borrowed from the branching thread, which found the same shape in a different subject: a sample of junctions whose impossible members are silently dropped looks clean and gives an answer that is wrong by more than the distance between the hypotheses being tested. The diagnostic there is one integer — attempted and retained. It is one integer here too.
The asymmetry between the two answers
There is a structural feature of this instrument that is easy to miss and worth stating on its own, because it decides how a survey should be designed.
A pair returned is nearly unambiguous. Three tests have been passed, the readout has named two integers, and those integers can be checked against a spiral count on the same stem. There is one way to get a wrong pair past all three tests — a window straddling a transition with one rung dominant — and it is detectable with a second window.
A refusal is highly ambiguous. Four causes, of which the sequence distinguishes none.
So the instrument is asymmetric in a way that most measurements are not. A thermometer reading twenty degrees and a thermometer reading nothing are both informative, the second saying the thermometer is broken. This readout’s silence says the plant might be quiet, or noisy, or fast, or badly sampled — or that the result of the century is sitting on the bench.
That asymmetry should shape the sampling. A survey that wants to establish a positive — that plants place organs one at a time, that this species is on the Lucas branch — can take specimens as they come and use the ones that return something, provided it reports the refusal rate and does not interpret it. A survey that wants to establish a negative has to control every one of the four causes on every specimen, which is a different and much more expensive design.
What this thread has and has not closed
Four phases have worked on the same question — what can be told from a finished plant about the process that made it — and it is worth setting out the ledger.
Closed. The recorded scatter cannot distinguish three kinds of noise; the lag-one correlation distinguishes the one that arrives after the placement from the two that arrive before it; the sign of that correlation reports whether the stem’s rise is falling; the spectrum’s main comb gives the smaller parastichy number and the second comb gives the larger; a lattice with no rule behind it has no comb at all; and both statistics come off one stem over a wide window of disturbance.
Not closed. Which of the two noises that arrive before the choice produced a given pattern — the field and the jostle are still not separated by anything measured. Whether a real plant’s disturbance is inside the readable window, which no model can answer. And the causes of a refusal, which is this essay.
Not attempted. The correlated jostle, carried over untouched from two phases ago: every disturbance in this thread is independent from node to node, and a real apex’s perturbations almost certainly are not. What a correlated disturbance does to the comb is unknown, and it is the kind of unknown that could remove the result rather than qualify it — a disturbance correlated at the parastichy number would manufacture the comb, and nothing here would notice.
That last one is the most important item in the phase’s leavings and it belongs here rather than in a summary, because it is the assumption every essay in this thread rests on and none of them tests.
Why this is progress
Three phases have failed to close this problem and it would be easy to read a fourth failure as a thread that should be dropped.
What has changed is that the failure now has a stated cause. The measurement phase recorded that the scatter alone cannot say which of three noises produced a pattern. The phase after found a statistic that separates one of the three from the other two. The phase after that found a second statistic and worried that the two wanted different plants. This phase shows they do not, and finds that the remaining obstacle is not about the statistics at all — it is that a null has four causes, three of which are properties of the specimen and the measurement rather than of the plant.
That is a problem with a design solution rather than an inferential one, and the design is written above. Which is a better place to leave a thread than where it was: a worry about signs, restated three times, never measured.
The line for the specification file
Three phases have added lines to the survey specification and this one adds the line that changes how it is read: a null is not a datum unless its cause is controlled.
Everything else in the specification is a cost — internodes, degrees of precision, nodes per rung. This is a design constraint, and it is the difference between a survey that can report “sixty per cent of stems returned a pair” as a fact about stems and one that can report it only as a fact about the survey.
The four, as a table
For the record, since the essay is mostly about them:
- too quiet — no pair, and a main comb near 0.98 — separated by the recorded scatter, and caught by the cap
- too disturbed — no pair and no comb at all — separated by the scatter
- the shoot too fast — no pair, no spacing winning by a band — separated by a second window
- the window badly placed — the same reading, and not separable from the one above
Two of the four are separated by a number a ruler gives. The other two are separated by measuring twice, and are not separated from each other at all — which does not matter, because the response to either is the same: move the window, or find a slower plant.
What is not in the table is the fifth possibility, that the plant’s organs were not placed one at a time. It is not in the table because nothing separates it from the others on a single stem, and that is the whole content of the essay.
Shares its objects with
Essays that name at least two of the same things, and that neither author linked.
- The test a plant could settle — both name autocorrelation, discrimination, divergence angle, evidence, falsifiability, identifiability, measurement, noise, sample size, specimen, survey
- What the pair costs — both name autocorrelation, discrimination, divergence angle, honest limits, identifiability, measurement, sample size, specimen, survey
- A comb is evidence of a rule — both name autocorrelation, discrimination, divergence angle, evidence, falsifiability, measurement, noise
- The band decides the answer — both name discrimination, evidence, honest limits, identifiability, measurement, sample size, specimen
- Two readings from one stem — both name autocorrelation, divergence angle, identifiability, measurement, noise, specimen, tolerance
- What one angle says about the next — both name autocorrelation, discrimination, divergence angle, identifiability, measurement, noise, tolerance
Named objects
A flat tag is an object no other essay names yet.
AutocorrelationDiscriminationDivergence angleEvidenceFalsifiabilityHonest limitsIdentifiabilityMeasurementNoiseRateSample sizeSpecimenSurveyToleranceUnderdetermination