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Okay, so now I can see your slides. Yeah,
in full screen mode. Perfect. Okay. You

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are ready, you can start.

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And it's Michael, I'm very glad to be
here, even virtually hope to be in Paris

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one day again. And really thank Allison
all the coordinators for this opportunity.

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So, in TMS we're wedged in in
understanding wide variety of systems.

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draw attention was brought to this
possibility of, of understanding very

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small systems, whether they

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behave collectively.

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Our interest essentially came from the
observation of the rich in high

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multiplicity PvP collisions. And this sort
of really two aspects of this. One of them

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is is whether we do see some approach to
hide dynamics when 100 Amex becomes

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applicable and they also the questions of
what is the initial state There's a small

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system look like

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ah

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What is it? What is the power spectrum of
fluctuations inside a small system. And so

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that's also what we're hoping to find

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from these studies. So

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so this this talk will focus on vn and
cumulus measurements. And these sort of

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flow correlations have been very helpful
in standing, the pressure that's in it in

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in heavier inclusions, and instead, we
want to use these techniques to look for

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collectivity in smaller systems. So today,
I'll pretty much focus on proton land and

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PvP and how we can try to subtract non
flow effects

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in those in those small systems.

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So first timers, Chris TPP pled

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So, a basic measurement would be to look
at the second moment the v2, and we can do

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this with just two particles four, six or
eight or even all particles in the event

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using the NGS and zeros. And so here on
the left we see proton proton versus

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proton lead versus lead lead. And we see
this general rise of v2 with a number of

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tracks. Now, in lead lead period, we see a
difference between the v2 with a just two

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particles and a larger PD cap, and then
the higher order measurements of v2, and

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we believe that this is because of the
these high order v four v 242. Six are

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better at subtracting non flow in Low
multiplicity, these two sets of

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measurements tend to come together. And
and potent, potent. We don't see such a

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difference between the two

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the different types of measurement. So

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let's look at another way of looking at
this data. We can look at v2 v3 v4. And

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there's different ways of tackling this
one is to try to subtract the very low

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multiplicity results from from the v2. And
this by definition forces, v2 sub to go to

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zero at Denver tax was this year. But when
we look at these measurements, we see non

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dual vetoes even down to very small
values. Until again, this question of, of

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always seeing is this real collectivity
and try to explore this more.

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So we've got also looked at different
particles, and not just all hydrants. So

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here we have charged hydrants versus
neutral counts versus lambdas, 90 lambdas.

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And we see different distributions, but
when we scale by these numbers by the

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number of quarks and look like the kinetic
energy divided by the number of quarks, we

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see this sort of universal scaling which
has also been seen, especially in in heavy

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hand collisions. And when we look at this
in P, P, again, we see the same thing it's

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clear difference in v2. For different
product features a functional PT,

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functional particles, we would express

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expect this in a hydrogen amical
situation.

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But when we scale by the number of quarks,
we get similar kinds of distributions for

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the different add ons in proton lead and
lead, lead, lead lead. Now hold on and

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lead lead this agreement is better, of
course, and see that there's some

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deviation in the product lead for the two
zeros. It's still the fact that the

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particles are so nicely like the Omega so
right on looks suggestive.

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So let's go to slide number nine. So

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here we're going to compare v2 and v3. And
in

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total on that and the lead, again, versus
the number of tracks. And again, we're

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we're doing different numbers of higher
order correlations, both in v2 and v3. And

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again, we see the the higher order
correlations seem to cut down v2, which is

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can we expect to be getting rid of non
flow, but it all methods seem to converge

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below about 100 tracks. So, another way of
looking at these data is to try to look at

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these ratios of v4 to v2. This is believed
to be sensitive to the ratios of the

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geometrical eccentricities.

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And when we look at this ratio for over v.

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So, v n for particle correlations of a VM
from two particle correlations, we see a

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gradual decrease with this is enough
agreement with what we expect from the

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scaling eccentricities. So, that that is
very

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here we see even higher order we see if we
compare different ratios now, like we have

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p 26324 and v two eight, a v2 six as a
ratio v2 for the future

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fy Two, two, we

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were pretty nice height. with very high an
ATV, we're very high statistics data, a

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slight increase with these trends and the
prediction is a reasonable agreement with

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with the ratio of geometrical
eccentricity. So that's nice. So, we

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suddenly we've been trying to move towards
using their cumulant methods to subtract

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non flow contributions. And so we have
these cumulative four particles, which of

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two orders and an M, and they can be, they
come as a ratio of the average cosine of

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these, this column here, which can be
broken down into n times the difference of

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two particles, multiplied by m times a
difference of four particles of two other

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particles.

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And then it could be talked about in the
ratio of the

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of

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products of Viet.

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Also we can use sub event methods to try
to break down our acceptance and then also

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try to get rid of short range correlations
to the effect of sub sub event. So here we

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see data from proton, proton, proton lead
and lead lead as a function of the number

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of tracks for these different order
correlators. And if we start perhaps on

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the on the right, you see the two three
correlator going down with multiplicity

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two for color going up. And so that change
occurring around about 100 tracks. We see

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in code on lead we see again this rapid
drop below 100 and then a flattening

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doesn't rise like that, but it is it
flattens, and then the PS two data looks a

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different kind of shape.

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Above 100 so not so,

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not quite the same as as I suppose a lead
and the lead lead I should say that the

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poteau lead clip access is somewhat
compressed in multiplicity. So, now we can

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another technique is to normalize these
key words by the RMS of the v2 and the v3

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and here we see proton proton proton lead.

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This rapidity between point three to three
gv

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and this is the second third correlator
can see a nice agreement between proton

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lead and lead lead. That's not such a good
agreement with with PGP. And again for the

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two for a moment again we see pulled on
ladder poaching lead ladder high

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multiplicity But somewhat different in pp.
So, if we sort of qualify this, this

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defense as a, we can add to this the scale
scale accumulates we can try to cut harder

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by using the sub event method to suppress
non flow even further. And we see again

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that we have these cumulants seem to have
got rid of non flow above about 100 below

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100 D no sub event method shoots up. So,
this is s two three and a similar

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situation we've seen in the s document two
four. I've wanted to for work in the know

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some event method shoots up, whereas the
higher multiple sub event methods Much

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more flat. So this is suggested that the
killer math, the suburban method is

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helping to get rid of modular.

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We can quantify this by looking at the
difference between the three and two

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suburban methods as a function of two sub
event. And we see for the two, three

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correlator, almost no difference. So it's
doing a very good job of suppressing non

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flow, there is a difference in

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for the two for correlator. Between

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and we, this this might be possible
because we may be seeing an effect of the

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event plan t correlation today. Not sure
why there's this difference in the two

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four correlated but event plan D
correlation may be reason.

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So finally, to our conclusions.

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We've been trying to explain that the wide
acceptance of CMS and ISIS two data sets

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to Canada in multiple ways to try to
suppress non flow. The data seem to be

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suggesting that collectivities present in
PP and perhaps p systems PNP systems with

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tracks of the order of 100. It's, it's
still, I'd certainly agree with the last

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speaker that its situation in PvP is not
clear. In the future, we will have a

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larger tracker and we will try to push to

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even smaller systems.

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Thank you everybody for your attention.

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Okay, thank you, Michael, for a very nice
talk. So now we have time for discussion.

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If you have a question, please press the
right hand button. Okay, so we have one

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bye you.

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Okay, so now you are unmuted please ask
your question.

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Hello, very nice results from CMS. I hope
you can hear me.

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Yes, I have questions.

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Yes. Oh, great. I have a small question
slide elevens. So this this results are

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really beautiful with the position man is
from CMS in Chula ATV. However, I guess

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the conclusion really depends on the
correlation between V and eccentricity

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coefficient, because we know that the
empty lead, we might not have a strong

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correlation or linear correlation between
the two. Therefore, these conclusion might

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be a little bit a little bit too strong.
If you compare initial state to the final

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state. Yeah.

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So I do hope set that inventory we can
have some smaller systems where we can

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control we have we have more variation in
the geometry. I think that has been an

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advantage to the rep program.

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And hopefully,

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we can we can have that more inventory. I
agree with you that it's It might be nice

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to have an oxygen oxygen on this plot
perhaps.

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That would be very interesting.

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Yeah. So I, I agree with you that this is
rather theoretical dependent.

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Do we have more questions? Sorry, I
couldn't respond. I have a question on

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slide eight. I want to know what is the
variable on the x axis?

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Oh, so what is it is the kinetic energy.
So what you do is you take the total

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energy of the particle and you subtract
the transverse, the mass of the system. So

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it's, it's, it's the kinetic kinetic
transverse energy, which is p x the square

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root of p x squared plus p y squared minus
m squared. I'm sorry. I apologize. I

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apologize for that. To find, and then it's
divided by the number of cooks. So you

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divide by two for me zones, and you divide
by FIFA barians. So I apologize that

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wasn't introduced to the problem. Thank
you.

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All right, do we have time for one more
question to this presentation?

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Okay, I don't see any. Okay. There's
another one here.

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Yeah, please go on

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version one, slide nine. I don't know if
there's new development in understanding

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of the low morphism region, while we see v
two four is higher than v two two.

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It's like mine

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because from from the Federation, corner
view, it's very hard to understand if v

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two four is higher than the two to

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eight Yeah, I would. You You You mean the
lead lead placed here?

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Give me this point. I wouldn't. I would
bet that it's the tie with it. I think

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within the systematic, it's consistent. I
agree. I agree with you. But I think we

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have the data in tables and I can look to
see if it's statistically. It there's

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actually a significant difference, but I
don't think so. This so i

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i wouldn't I would base that on done and
the one point there.

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All right. Thank you, Michael. I think we
have to switch to the last presentation.