EmoClass
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10 values
EmoAct
float64
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EmoVal
float64
1
7
EmoDom
float64
1
7
SpkrID
int64
1
3.33k
Gender
stringclasses
2 values
Split_Set
stringclasses
2 values
transcript
stringlengths
1
353
emotion2vec_features
listlengths
1
1
H
4.4
5.2
4.6
357
Female
Train
super good deal. so you have investment of money [inaudible 00:06:48]
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N
4
3.2
4.6
357
Female
Train
this is really just a couple people in a dark room somewhere forking purecoin.
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U
4.2
4.4
4
357
Female
Train
so therefore, are all cryptocurrency securities?
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H
4.2
5
4.4
357
Female
Train
but we've worked at coin center to develop a framework that helps answer that question. hope [inaudible 00:07:04]
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N
3.4
4
3.8
357
Female
Train
could narrowly apply to the specific facts of this particular case.
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N
4.6
3.6
4
357
Female
Train
basically. so, recognizing that this is a looming issue, and [inaudible 00:07:14]
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S
3.2
4
3.6
357
Female
Train
just a statute or a regulation with enumerated categories-
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N
2.6
3.2
3.8
357
Female
Train
... you're going to potentially be subject to us regulations and-
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X
3.6
4.4
4.4
357
Female
Train
... if that country has extradition, which most friendly countries do.
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X
3.4
4
4.4
357
Female
Train
so we have this looming threat-
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X
3.4
4.8
4.8
357
Female
Train
... and the summer of 2015 was present a framework to the sec that we felt would be helpful for them in first understanding how these technologies work.
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N
3.8
4.6
4
357
Female
Train
it was a small group of people developing this thing and promising these integrations.
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X
4
4.2
4.2
357
Female
Train
it's a common enterprise, but not the kind of common enterprise that we regulate as a issuer of securities. and-
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N
3.2
4.4
3.6
357
Female
Train
[inaudible 00:07:55] thing. so the way bitcoin does it, the way ethereum does it, the way paycoin did it.
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H
4.4
5
4.6
357
Female
Train
and you can map them to the howey test.
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X
3.8
3.4
4
357
Female
Train
say, this amount of decentralization in mining and in software development makes it look like we don't have a common enterprise.
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X
4.8
3.4
4.6
357
Female
Train
even just josh garza contrast paycoin when it comes to, was there distributed mining, not-
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S
3.4
2.8
3.6
357
Female
Train
... [inaudible 00:08:22] going concern that it's selling its assets as basically equity stake.
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H
3.4
4.6
4
357
Female
Train
completely understand the joy of suing a co-op board.
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N
4
3.8
4.2
357
Female
Train
tenant for example, sued the co-op board for securities fraud.
[ { "feats": [ 0.10485539585351944, -0.17097915709018707, 0.14150770008563995, -0.12477394193410873, 0.7280508279800415, 0.24245645105838776, 0.0024131250102072954, 1.090564489364624, 0.8235735893249512, 0.07006394863128662, -0.780691385269165, ...
S
3.8
3.2
4.2
357
Female
Train
so these people, these organizations that [inaudible 00:08:41]
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X
4.6
5.2
4.4
308
Male
Train
because the ethereum is a platform for decentralized computing that makes it very easy to issue these tokens.
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X
3.2
3.6
3.6
308
Male
Train
the only way to ever authoritatively say that something is or is not a security, is to be a federal judge.
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O
4.6
3.2
4.6
308
Male
Train
ideally, if the thing had worked the way it was supposed to work-
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N
3.6
3.8
4
308
Male
Train
... it would be only the members who would vote on its use.
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N
4
4.6
4.4
308
Male
Train
anyway.investment of money, common enterprise. we're looking good for the dow being a security. those two pros,
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A
3.4
3.8
4
308
Male
Train
the damn website the dow is
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X
4.8
4.2
5
308
Male
Train
and those giant investors could vote to send everybody's money to themselves with no chance of
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N
4
4.4
4
308
Male
Train
it's of interest to all who follow ico regulation,
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X
4.2
4.8
3.8
308
Male
Train
a and their event is a good place to gain an insight into the culture of the group.
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X
3.2
4.6
4.2
308
Male
Train
it's just a really worthwhile event to attend .
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X
4.6
4.8
5.2
308
Male
Train
but still publicly coming forward and minimizing it. also, it was interesting if you look through the comments
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H
3.2
4.8
4.8
308
Male
Train
on october 26th, the team hopes to have raised 30 million swiss freights.
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S
3.2
3.6
3.6
308
Male
Train
we need data that's constantly being produced.
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S
3.2
2.8
2.8
552
Male
Train
new measurements are pouring in various sources such as iot sensors.
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N
2.6
4.2
3.6
552
Male
Train
is creating a decentralized peer-to-peer network for data delivery.
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S
3.6
3
4
552
Male
Train
so a data producer can publish new data points, which instantly get delivered to all the valid subscribers,
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S
3.8
3.6
4
352
Male
Train
which means that whenever you produce valuable data that somebody else is interested in,
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N
4.2
4.6
4.2
352
Male
Train
so basically a data stream economy is born where both people and machines can trade data streams.
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X
4.2
4.8
4.4
351
Male
Train
this is huge. it basically enables machines to produce and sell data and interact autonomously without human intervention.
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U
5.4
4.6
4.6
352
Male
Train
well basically, yes. so what we're building to go
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N
3.2
3.8
4
352
Male
Train
is a separate network that quite tightly integrates with the ethereum network,
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X
3
3.8
3.6
351
Male
Train
identity, permission control, and things like this.
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X
4.2
3
3.8
351
Male
Train
plus binds some kind of producing identity to all the data points so,
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N
3.2
4
3.8
351
Male
Train
we can basically know which ethereum account is responsible for certain data or which ethereum account is responsible for receiving certain data.
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N
3.8
3.6
3.6
351
Male
Train
so this way we can already tackle data driven real world use cases where the data quantities could be quite large.
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N
4
4
4.2
352
Male
Train
i mean, a system could easily produce like a million events per second,
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S
2.8
3.6
3.8
278
Female
Train
for the streamer network, but obviously a million transactions per second would be huge overkill for all current blockchains.
[ { "feats": [ 0.16986966133117676, -0.14711607992649078, 0.175368994474411, -0.003910293336957693, 0.6449137330055237, 0.47060897946357727, 0.038989003747701645, 1.073130488395691, 0.677506685256958, 0.04683976620435715, -0.888753354549408, ...
O
4
4.2
4.2
278
Female
Train
can you break down that terminology into something that kind of connects with a real life use case?
[ { "feats": [ 0.25169703364372253, -0.13525664806365967, 0.13840647041797638, -0.05731091648340225, 0.6793534159660339, 0.3066554069519043, 0.0936860516667366, 1.1381224393844604, 0.7702559232711792, 0.09461548924446106, -0.765217661857605, ...
N
3.8
3.8
3.4
278
Female
Train
there's a trade, and all of these are events in the system ,
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N
4.2
4.4
4
278
Female
Train
for example, let's say there would be a network of temperature sensors or,
[ { "feats": [ 0.11673649400472641, -0.27466708421707153, 0.1753775030374527, -0.012817195616662502, 0.6647428274154663, 0.3779093325138092, 0.09538819640874863, 1.1465150117874146, 0.7607228755950928, 0.023229677230119705, -0.8855891823768616, ...
S
3.2
3.2
3
278
Female
Train
which might be interested in that data for their own purposes.
[ { "feats": [ 0.12282731384038925, -0.22864370048046112, 0.2348746806383133, 0.05617731437087059, 0.7375234961509705, 0.4398232400417328, -0.1279572695493698, 1.2173080444335938, 0.8052695989608765, 0.057847850024700165, -0.8884720802307129, ...
N
3.4
4.8
4.2
278
Female
Train
even now, i mean the metrics of our skype call is going somewhere and,
[ { "feats": [ 0.005988318473100662, -0.23691995441913605, 0.20930632948875427, 0.04371245205402374, 0.665065348148346, 0.29044046998023987, 0.06341303884983063, 1.1644139289855957, 0.7614902853965759, -0.08665934950113297, -0.7123782634735107, ...
X
3.6
3.2
3.6
278
Female
Train
in this case, ethereum, and the value of that data is somehow tokenized,
[ { "feats": [ 0.18000072240829468, -0.2885389029979706, 0.22387920320034027, -0.09413740783929825, 0.7804782390594482, 0.2689639925956726, 0.010476919822394848, 1.3750098943710327, 0.8664245009422302, -0.04213474318385124, -0.6580237746238708, ...
S
2.6
3
3.4
278
Female
Train
and maybe i want to cover my gas cost by selling my location to advertisers,
[ { "feats": [ 0.09373842179775238, -0.2052070051431656, 0.15202103555202484, -0.001964724389836192, 0.7389532327651978, 0.4606698751449585, 0.19494369626045227, 1.2179887294769287, 0.7583756446838379, -0.01683702878654003, -0.8976213932037354, ...
S
3.4
3
3.6
278
Female
Train
i mean the license can be quite arbitrary since they can be implemented as smart contracts.
[ { "feats": [ 0.10164514929056168, -0.2158835381269455, 0.1503685712814331, -0.1021120548248291, 0.6786201596260071, 0.4299492835998535, 0.008559320122003555, 1.0601999759674072, 0.6884608268737793, -0.015959760174155235, -0.9368862509727478, ...
X
3.2
4.6
3.8
278
Female
Train
so i can basically define the terms quite freely and how the payment system works
[ { "feats": [ 0.07494675368070602, -0.1574224829673767, 0.21227604150772095, 0.006782034412026405, 0.7658303380012512, 0.35422906279563904, 0.02654905803501606, 1.113749623298645, 0.7304598689079285, 0.03457925468683243, -0.8705424070358276, ...
H
4
5.2
4.4
278
Female
Train
yes, exactly. exactly. let's start with the decentralization part.
[ { "feats": [ 0.056695230305194855, -0.20156274735927582, 0.22835977375507355, -0.11007630079984665, 0.5415347218513489, 0.408593088388443, 0.033472612500190735, 1.0833572149276733, 0.5950289964675903, -0.0920870378613472, -0.8070482015609741, ...
O
4.4
2.8
4.8
278
Female
Train
so how do we actually decentralized the network?
[ { "feats": [ 0.14735181629657745, -0.21551752090454102, 0.1476788967847824, 0.0849611759185791, 0.726966917514801, 0.29656165838241577, -0.007021073717623949, 1.2898753881454468, 0.8236309289932251, 0.06619071960449219, -0.6870142221450806, ...
S
3.6
3.2
4.4
278
Female
Train
there needs to be some kind of incentive for anyone to run the nodes and,
[ { "feats": [ 0.14701294898986816, -0.11079101264476776, 0.17492541670799255, -0.011334383860230446, 0.7080014944076538, 0.4378594160079956, 0.15041270852088928, 1.1489697694778442, 0.6845870614051819, 0.07828833907842636, -0.8388386368751526, ...
S
3
3.8
3.4
278
Female
Train
superficial math problem that contributes the proof of,
[ { "feats": [ 0.07347088307142258, -0.19754190742969513, 0.14138852059841156, 0.15129315853118896, 0.6489145159721375, 0.5275353789329529, -0.0027606699150055647, 1.2306791543960571, 0.7930249571800232, 0.07416992634534836, -0.8536707758903503, ...
H
3.4
4.6
3.4
278
Female
Train
just the infrastructure that enables all of this and various applications can be developed onto
[ { "feats": [ 0.12066074460744858, -0.19006185233592987, 0.13006338477134705, 0.020553136244416237, 0.656801700592041, 0.33865052461624146, 0.03251338005065918, 1.1365723609924316, 0.6868798732757568, 0.035096485167741776, -0.7971217632293701, ...
X
2.6
3.6
3
278
Female
Train
stream. and this is of course how we also achieve data privacy in a network.
[ { "feats": [ 0.06947871297597885, -0.252677321434021, 0.20489968359470367, -0.0686960220336914, 0.7434354424476624, 0.3718646466732025, 0.05306766927242279, 1.209334135055542, 0.7000837326049805, 0.039542581886053085, -0.7613322138786316, 0...
H
3.6
4.8
3.6
278
Female
Train
were beginning to be able to monitor,
[ { "feats": [ 0.11527663469314575, -0.2506515681743622, 0.22124123573303223, -0.04939156398177147, 0.8307870626449585, 0.47708165645599365, 0.10536973178386688, 1.2527767419815063, 0.751396656036377, -0.048855431377887726, -0.9663414359092712, ...
S
3.8
4.2
3.8
278
Female
Train
given that the volume of the data is growing exponentially as we know
[ { "feats": [ 0.1688620001077652, -0.3046954870223999, 0.2451360672712326, -0.06431999802589417, 0.7836460471153259, 0.4025656282901764, -0.023896535858511925, 1.2617177963256836, 0.7512611150741577, -0.050357721745967865, -0.903681218624115, ...
X
3.8
3.2
4.2
789
Female
Train
what will be too much data that none of your patterns too difficult.
[ { "feats": [ 0.13062913715839386, -0.20356044173240662, 0.27591028809547424, 0.04579019546508789, 0.7467273473739624, 0.43640628457069397, 0.04044955596327782, 1.2359967231750488, 0.6766435503959656, -0.07198375463485718, -1.033478856086731, ...
X
3.2
4.2
4.4
790
Male
Train
what sets us apart from many other projects in this space is that we actually have something that's up and running at the moment ,
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H
4.6
5.6
4.6
790
Male
Train
without leaving out the e. so,
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S
3.2
3.6
3.4
790
Male
Train
many are hoarding the domains for dictionary words.
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X
4.2
4.8
3.8
790
Male
Train
mme, who is famous for running the ethereum crowd sale.
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N
4.6
4.4
4
790
Male
Train
obviously you guys done a whole lot more since ethereum launched.
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X
4.4
4.4
4
789
Female
Train
oh yes, we were happy to do that. the launch of ethereum mass, the first tokens,
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X
3.4
3.6
4.4
790
Male
Train
our first advice area was to find out whether or not they fall under,
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H
3.2
4.4
4
790
Male
Train
we did about 25 token generating events.
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U
4.4
3.6
5
789
Female
Train
so we would have never thought about what kind of wave of work is now exploding over our heads.
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N
3
4.2
3.8
790
Male
Train
you see, switzerland has whatever is under monitor, transmittance or exchange service is on the the aml regulation.
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N
4.4
4
4.4
789
Female
Train
few professionally monitor transmits and or exchange can be crypto,
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X
4.2
3.6
4.2
789
Female
Train
does not fall. the swisslow on the anti money laundering legislation,
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N
3.4
4
3.4
326
Female
Train
which are the money transmittance and exchange functions.
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A
4.2
2.8
4.6
326
Female
Train
are focused on the exchange from fiat into digital and digital into fiat.
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A
4.4
2.8
4
326
Female
Train
so if you actually participate in a token generating event,
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N
3.6
3.2
4.6
326
Female
Train
so that's why we do not regulate a,
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X
4.4
3.8
4.2
326
Female
Train
participation in a token generating event. under the anti money laundering legislation,
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N
3.8
4.4
4.4
326
Female
Train
you have this investor interest approach.
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N
4.2
4
4.4
326
Female
Train
so in a way, the test is a little bit wake
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O
4.6
3.6
4.4
326
Female
Train
how you apply, how we test in order to define whether or not it falls under the security regulations or not.
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X
4
3.6
4.2
326
Female
Train
and that makes it difficult to decide whether or not your token you generate is now falling on the securities law or not in switzerland.
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H
4.2
4.8
4.4
326
Female
Train
and that's the reason why the assessment is easier and it actually provides you more legal certainty.
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N
4.4
4.2
4
325
Male
Train
and i think this is the advantage we have in our jurisdictional environment.
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U
3.2
5
4.6
326
Female
Train
that's a good question. if we do a token generating event, we-
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O
3.6
3.8
4
326
Female
Train
... always consult our us legal team, and there are some token generating event which we would say, okay.
[ { "feats": [ 0.10448437929153442, -0.16562725603580475, 0.2000935673713684, -0.049766261130571365, 0.8067592978477478, 0.465472012758255, 0.07904565334320068, 1.237573266029358, 0.6992622017860413, 0.008673793636262417, -0.9138577580451965, ...
S
4.8
3.8
4.2
326
Female
Train
so if you donate something to a foundation-
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X
3.6
3.6
4.8
326
Female
Train
... and this is a mandatory audit-
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N
3.8
3
3.8
325
Male
Train
... that's the reason why you cannot use a foundation structure for transmitting funds.
[ { "feats": [ 0.0722498968243599, -0.17796596884727478, 0.056408774107694626, -0.06009174510836601, 0.6252050995826721, 0.39427006244659424, 0.01749391108751297, 1.1089078187942505, 0.7955319881439209, 0.04461907222867012, -0.9511203169822693, ...
N
4.2
3.6
3.8
325
Male
Train
and you can only use the funds according to purpose, controlled by an audit company and by supervisory authority.
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X
3.8
4
4.4
325
Male
Train
so you see, the concept is different. in the us-
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H
4.4
3.6
4.2
325
Male
Train
... it can be possible that the foundation is collecting the funds and is then transmitting the-
[ { "feats": [ 0.020187202841043472, -0.06428992003202438, 0.18029499053955078, 0.05438344180583954, 0.7158982157707214, 0.3447897434234619, -0.0024950450751930475, 1.1057509183883667, 0.7685319781303406, 0.016183694824576378, -0.9484643340110779, ...
H
4.4
4.4
4.4
326
Female
Train
you can do a lot of things. you can support whatever you want or-
[ { "feats": [ 0.044556669890880585, -0.27967214584350586, 0.1852552890777588, -0.0012907274067401886, 0.8746985793113708, 0.4650559425354004, 0.09198124706745148, 1.4441956281661987, 0.8512732982635498, 0.009033748880028725, -0.853873610496521, ...
X
4.2
4
4.6
326
Female
Train
... one structure.it's not for every token generating event-
[ { "feats": [ 0.07673870027065277, -0.11018626391887665, 0.14714767038822174, -0.10308142006397247, 0.6607342958450317, 0.39416930079460144, -0.09226997941732407, 1.2157665491104126, 0.6818981170654297, -0.047552164644002914, -0.9263961315155029, ...
N
3.6
4.2
4.4
326
Female
Train
... foundation structure. now regarding the-
[ { "feats": [ 0.08706574887037277, -0.10882046818733215, 0.16413603723049164, 0.06461954861879349, 0.6356170773506165, 0.3324968218803406, -0.014646882191300392, 1.0968132019042969, 0.660179078578949, 0.0584760420024395, -0.8281164765357971, ...