df_clean$entire_sample_period
in Dummy umwandeln
df_clean$entire_sample_period
in Dummy umwandeln
To-do Wir haben hier einen Fehleintrag von 20024 drinnen, der muss noch ausgebessert werden. 1937, 1939, 1980, 1982, 1985, 1986, 1987, 1990, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2012, 2013, 2017, 20024 Ist das eigentlich 2024?
Dasselbe wie voher, 20024 checken
df_clean$treatment_group
df_clean$wtr_hours_new
Es gibt hier NAs, bitte anschauen
df_clean$data_type
drei Dummies daraus machen
Monthly
Es gibt nur 20 davon... wie damit umgehen?
df_clean$workers_working_hours
Eventuell für Unterscheidung Vollzeit/Teilzeit wichtig! Wie können wir das konzeptuell analysieren?
df_clean$level_analysis
Was bedeutet der Wert Aggregate
hier?
df_clean$sector_type
Ich sehe zwei Möglichkeiten das zu codieren:
Manufacturing
und anderen ? (Agriculture hat nur 6 obs..)df_clean$firms_size
Die Woche diskutieren
df_clean$econometric_issues_techniques
df_clean$regression_controls_description
Mehrere Dummies daraus bauen
df_clean$workers_income
Evt. nutzbar? "Wer kann es sich leisten, AZV zu machen"?
df_clean$econometric_model_design
Die Woche dkisutieren
df_clean$control_group
df_clean$regression_fixed_effects_description
ähnlich wie andere Dummies fixed-effects-dummies bauen
df_clean$dependent_variable_form
Wichtig!
df_clean$dependent_variable_name_category
df_clean$ts_or_se_information
Evt. Dummy bauen ob SEs clustered wurden oder nicht?
df_clean$before_policy_implementation
Sollen wir das als Kontrolle benutzen?
df_clean$independent_variable_wtr_form
Missed variable - check `fct_collapse` command
Das sollten eigentlich alle originalen value labels sein - überprüfen!
Duwendag
Wir brauchen einen d_Duwendag - Dummy
df_clean$preferred_estimate
Falls wir's benutzen wollen müssen wir die Variable überarbeiten.
Vorschlag: Main result vs. robustness check
author_1
Eine Tabelle erstellen welche Autoren als irgendein Author (first-last) in papers auftauchen und relativen Anteil ausrechnen
Being unemployedDummy (0: Being occupied/inactive or 1: Being unemployed)Employed, unemployed or inactive (individual)Dummy (0 or 1)4
Kombination löschen
Being inactiveDummy (0: Being employed/unemployed or 1: Being inactive)Employed, unemployed or inactive (individual)Dummy (0 or 1)4
Kombination löschen
Transition to a larger size establishmentDummy (Current job: 0, New job (larger size establishment): 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14
Anschauen um welche Effekte es hier genau geht
Individual is unemployed, employed at a large firm or employed at a small firm at time tDummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t)Employed, unemployed or inactive (individual)Dummy (0 or 1)16Individual is unemployed, employed at a large firm or employed at a small firm at time t+2 (the last year in each panel)Dummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t + 2)Employed, unemployed or inactive (individual)Dummy (0 or 1), interaction20Job to non-employmentDummy (Current job: 0, New job: 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14
Anschauen um welche Effekte es hier genau geht
dependent_variable_name_category == “Employment (growth)”
Für alle Variablen ansehen was genau gemessen wird, + Formeln heraussuchen. Im Idealfall können wir alles mit Employment per person kombinieren.
Unit gap, overtime hour
Alle Zeilen die diesen Wert haben rausschmeißen
Job-Job-TransitionDummy (Current job: 0, New job: 1, Nonemployment: 2)OtherDummy (0 or 1)28Staying at jobDummy (Current job: 0, New job: 1, Nonemployment: 2)OtherDummy (0 or 1)14
Nochmal genauer anschauen
Job growth rate (in %)
Sind das besetze Jobs oder ausgeschriebene JObs?
Differences and logEmployment (number of persons)Standard hours, log and differences
Checken:
Standard workweek, log
Anschaune ob es vergleichbar ist
The field rewards researchers who can translate expensive experimentation into deep, portable ideas.
nice
Description
The nostalgia and joy associated with toy train rides in Delhi. The abandoned toy train is charming and simple. Serving as a poignant reminder of carefree days.
9. Geolocation
حداقل سه تا از 4 آپشن رو لازم داریم
8. Cluster map
حتما لازم است
7.2. Requiring and excluding facet values
حتما لازم است
Janie said archly and fixed him back in bed. It was then she felt the pistol under the pillow. It gave her a quick ugly throb, but she didn’t ask him about it since he didn’t say.
Foreshadowing
Mrs. Turner’s brother was back on the muck and now he had this mysterious sickness. People didn’t just take sick like this for nothing.
He doesn't even know he has rabies
Tea Cake took it and filled his mouth then gagged horribly, disgorged that which was in his mouth and threw the glass upon the floor. Janie was frantic with alarm.
RABIES SYMPTOMS
He bought another rifle and a pistol and he and Janie bucked each other as to who was the best shot with Janie ranking him always with the rifle.
They're loaded upp
Atmungsaktive
change to lorem ipsum
Schmerzlinderung für Hände bei Arthritis, Karpaltunnel, Zerrungen oder anderen Gelenkerkrankungen.
CHANGE TO LOREM IPSUM
MODULE 1 - ENTWICKEIT CHANGE TO LOREM IPSUM
Alice’s money gets assigned to Carol, and all debts are set off, without anynew relationship between Alice and Carol.
I love the way this works.
The major difference with Cycles is that Alice doesn’t simplypublish a transaction to send $10 to Bob; she first declares that she owes Bob $10
I love how this shifts the perspective of money, into a trust base commitment to each other
Perhaps Alice’s counterparty Bob doesn’t accept stablecoins;he only accepts ATOM. However, he may owe Carol $10, and Carol does accept the stablecoin. Byhaving Alice, Bob, and Carol all declare their intents, Cycles can transfer Alice’s stablecoin directlyto Carol (without them being aware of each other) and publish set-off notices for everyone
I love the way how there is flexibility for all different kinds of forms of money and crypto!
At regular intervals (e.g. daily, monthly),solvers execute and find solutions that clear the most obligations for the most people with the leastamount of liquidity, based on the published intents
What is your experience around the most optimal interval? Is this a manual process for certain users in the platform or is this automated?
Our defaultsolver is a min-cost max-flow algorithm called Multilateral Trade Credit Set-off (MTCS
I am curious about the computational complexity of this algorithm. Especially when the userbase of the platform will scale up in the future. Did you already do any benchmark tests with larger userbase?
our proposed payment system is designed without such intermediaries, and is focused onliquidity saving via set-off.
Will Cycles also be connected (in the future) with existing clearinghouses or other clearing DeFi protocols?
onnect their internal accounting system to a global network that optimizes theclearing of credits and debts using the available sources of liquidity
Is there any information available on the onboarding process of SME's? As it seems to be a protocol heavy environment, I would state the importance of good UX abstraction. I am curious of the UX interface and the terminology used, so SMEs have a smooth onboarding process
How feasible is it to onboard SMEs into a protocol-heavy environment like this? What UX abstractions will hide complexity of “obligations, tenders, and acceptances”?
both groups had startedseventh grade with equivalent achievement test scores
Starting at the same time or even later than the other person is not a problem with the right growth mindset.
they would sim-ply study more or study differently the next time
GOOD IDEA
if youworked hard it meant that you didn’t have ability, andthat things would just come naturally to you if you did.
Negative at first, dangerous belief that effort = failure sign.
This explains why some students give up quickly when things get tough.
we find that students with a fixed mindsetcare so much about how smart they will appear that theyoften reject learning opportunities
Fixed mindset can block progress even when opportunities are helpful. Can we say the opposite? Because they deny too many opportunities to get better, they passively develop a fixed mindset from a young age.
hey don’t necessarily believe that everyone has thesame abilities or that anyone can be as smart as Einstein,but they do believe that everyone can improve theirabilities. And they understand that even Einstein wasn’tEinstein until he put in years of focused hard work
Not many people are born geniuses, but there are many geniuses who have succeeded through efforts.
growth mindset were much more interested inlearning than in just looking smart in school.
Growth mindset = value learning, not just appearance. I sometimes worry about looking smart too:(((
As the students entered seventh grade, wemeasured their mindsets (along with a number of otherthings) and then we monitored their grades over thenext two years
Longitudinal study = stronger evidence, not just a snapshot
A fixed mindset makes chal-lenges threatening for students (because they believethat their fixed ability may not be up to the task
Real examples, they believe that they can never do that with their poor brain, don't even try because of the fear. Overtime, this bad belief make their intelligence be fixed and this goes on and on until they change.
studentswith this mindset worry about how much of this fixedintelligence they possess
Some geniuses are born with natural talent, but not everyone is like that. The truth is that everyone is born with a certain level of intelligence, but it is not necessarily fixed.
Internal and External Motivation
This shows the article is part of a larger unit/theme about motivation. Will the article argue that growth mindset is a form of internal motivation?
These different beliefs, or mindsets, cre-ate different psychological worlds
That's important to believe and confident in yourself. Just a little bit change in mindsets, there can be change the whole worlds.
Tea Cake, Ah don’t speck you seen his eyes lak Ah did. He didn’t aim tuh jus’ bite me, Tea Cake. He aimed tuh kill me stone dead. Ah’m never tuh fuhgit dem eyes. He wuzn’t nothin’ all over but pure hate. Wonder where he come from?”
Rabies brooo
Dey oughta know if it’s dangerous.
The perception of white people was that they were highly educated and it was common to think that way
cents
cent (pas de s)
5€
espace insécable entre 5 et €
3€
espace insécable entre 3 et €
M 2
pas d'espace entre M et 2
evue Alternatives
idem, paragraphe coupé à resolidariser
références pour mon travail,
revenir à la ligne, ne pas couper le paragraphe
Mario Draghi on the (absence of) EU clout in current geopolitical climate, and ways to increase it.
4539
DOI: 10.7554/eLife.95887
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SciCrunch record: RRID:BDSC_4539
81213
DOI: 10.7554/eLife.95887
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38424
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DOI: 10.7554/eLife.95887
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55851
DOI: 10.7554/eLife.95887
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48101
DOI: 10.7554/eLife.100890
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SciCrunch record: RRID:BDSC_48101
strain B6SJL-Tg, APPSwFlLon, PSEN1*M146L*L286V, 6799Vas/J, MMRRC
DOI: 10.3390/nu17162679
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Curator: @AleksanderDrozdz
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35785
DOI: 10.3390/jdb13030030
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SciCrunch record: RRID:BDSC_35785
35706
DOI: 10.3390/jdb13030030
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SciCrunch record: RRID:BDSC_35706
33704
DOI: 10.3390/jdb13030030
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35388
DOI: 10.3390/jdb13030030
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SciCrunch record: RRID:BDSC_35388
40931
DOI: 10.3390/jdb13030030
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SciCrunch record: RRID:BDSC_40931
Bloomington Drosophila Stock Center
DOI: 10.3390/ijms26167954
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SciCrunch record: RRID:SCR_006457
BL 4590
DOI: 10.3390/cimb47080626
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SciCrunch record: RRID:BDSC_4590
B6SJL-Tg(APPSwFlLon,PSEN1M146LL286V)6799Vas/Mmjax, RRID, was obtained from the Mutant Mouse Resource and Research Center (MMRRC)
DOI: 10.3390/biom15081164
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1859
DOI: 10.26508/lsa.202503246
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SciCrunch record: RRID:BDSC_1859
64349
DOI: 10.26508/lsa.202503246
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9330
DOI: 10.26508/lsa.202503246
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5905
DOI: 10.2147/DDDT.S525366
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BDSC_35152
DOI: 10.21203/rs.3.rs-7159889/v1
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BDSC_32403
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BDSC_44417
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BDSC_65879
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BDSC_63622
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BDSC_54059
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BDSC_35371
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BDSC_38315
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DOI: 10.17912/micropub.biology.001718
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1767
DOI: 10.1523/ENEURO.0582-24.2025
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51635
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CRL-3216
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CCL-185
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CRL-1586
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GUS-p53
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Gal80ts
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6598
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y1w1118; vkg-GFP (vkgCC00791)
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BDSC #52220
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BDSC #83347
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BDSC #50540
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RRID:CVCL_0063
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RRID:CVCL_0019
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BL#5427
DOI: 10.1111/gtc.70040
Resource: RRID:BDSC_5427
Curator: @maulamb
SciCrunch record: RRID:BDSC_5427
BL#7906
DOI: 10.1111/gtc.70040
Resource: RRID:BDSC_7906
Curator: @maulamb
SciCrunch record: RRID:BDSC_7906
HTB-96
DOI: 10.1101/2025.08.27.672337
Resource: (RRID:CVCL_0042)
Curator: @dhovakimyan1
SciCrunch record: RRID:CVCL_0042
Addgene 12253
DOI: 10.1101/2025.08.25.672222
Resource: RRID:Addgene_12253
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_12253
Addgene 12251
DOI: 10.1101/2025.08.25.672222
Resource: RRID:Addgene_12251
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_12251
Addgene 12259
DOI: 10.1101/2025.08.25.672222
Resource: RRID:Addgene_12559
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_12559
Addgene 120378
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_120378
Addgene 131038
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_131038
Addgene 130953
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_130953
Addgene 120376
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_120376
Addgene 129744
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_129744
Addgene 129743
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_129743
Addgene 129742
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_129742
Addgene 120372
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_120372
Addgene 129742
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_129742
Addgene 130959
DOI: 10.1101/2025.08.25.672222
Resource: None
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_130959
stock #002014
DOI: 10.1101/2025.08.25.672167
Resource: (IMSR Cat# JAX_002014,RRID:IMSR_JAX:002014)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:002014
RRID: CVCL_7526
DOI: 10.1101/2025.08.25.672161
Resource: (Coriell Cat# GM12878, RRID:CVCL_7526)
Curator: @dhovakimyan1
SciCrunch record: RRID:CVCL_7526
Addgene, Cat #12260
DOI: 10.1101/2025.08.24.671070
Resource: RRID:Addgene_12260
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_12260
Addgene, Cat #52961
DOI: 10.1101/2025.08.24.671070
Resource: RRID:Addgene_52961
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_52961
CRL-1573
DOI: 10.1101/2025.08.24.671070
Resource: (DSMZ Cat# ACC-305, RRID:CVCL_0045)
Curator: @dhovakimyan1
SciCrunch record: RRID:CVCL_0045
Addgene, Cat #12259
DOI: 10.1101/2025.08.24.671070
Resource: RRID:Addgene_12259
Curator: @dhovakimyan1
SciCrunch record: RRID:Addgene_12259
stock number: 000664
DOI: 10.1101/2025.08.22.671764
Resource: RRID:IMSR_JAX:000664
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:000664
RRID:IMSR_JAX:021160
DOI: 10.1101/2025.08.22.671724
Resource: (IMSR Cat# JAX_021160,RRID:IMSR_JAX:021160)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:021160
9750
DOI: 10.1101/2025.08.14.670187
Resource: RRID:BDSC_9750
Curator: @maulamb
SciCrunch record: RRID:BDSC_9750
RRID:MMRRC 0384840-JAX
DOI: 10.1101/2025.08.08.669361
Resource: None
Curator: @AleksanderDrozdz
SciCrunch record: RRID:MMRRC_038484-MU
BDSC 34687
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_34687
Curator: @maulamb
SciCrunch record: RRID:BDSC_34687
BDSC 42488
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_42488
Curator: @maulamb
SciCrunch record: RRID:BDSC_42488
BDSC 50652
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_50652
Curator: @maulamb
SciCrunch record: RRID:BDSC_50652
BDSC 35259
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_35259
Curator: @maulamb
SciCrunch record: RRID:BDSC_35259
BDSC 58496
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_58496
Curator: @maulamb
SciCrunch record: RRID:BDSC_58496
BDSC 43962
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_43962
Curator: @maulamb
SciCrunch record: RRID:BDSC_43962
BDSC 64759
DOI: 10.1101/2025.08.08.669325
Resource: RRID:BDSC_64759
Curator: @maulamb
SciCrunch record: RRID:BDSC_64759
BL-25374
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_25374
Curator: @maulamb
SciCrunch record: RRID:BDSC_25374
BL-51327
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_51327
Curator: @maulamb
SciCrunch record: RRID:BDSC_51327
BL - 41,163
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_41163
Curator: @maulamb
SciCrunch record: RRID:BDSC_41163
BL-38933
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_38933
Curator: @maulamb
SciCrunch record: RRID:BDSC_38933
BL-61501
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61501
Curator: @maulamb
SciCrunch record: RRID:BDSC_61501
BL-61400
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61400
Curator: @maulamb
SciCrunch record: RRID:BDSC_61400
BL-61424
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61424
Curator: @maulamb
SciCrunch record: RRID:BDSC_61424
BL-61383
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61383
Curator: @maulamb
SciCrunch record: RRID:BDSC_61383
BL-61416
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61416
Curator: @maulamb
SciCrunch record: RRID:BDSC_61416
BL-61425
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61425
Curator: @maulamb
SciCrunch record: RRID:BDSC_61425
BL-61391
DOI: 10.1080/21505594.2025.2549497
Resource: RRID:BDSC_61391
Curator: @maulamb
SciCrunch record: RRID:BDSC_61391