Tarefa paper_repro.cheng_hoekstra_2013.tab5_pb_c2.tool

paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9df

Veredito

passouPassou em todas as verificações obrigatórias.

Pergunta feita ao analista

Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.

Valores esperados e de onde vêm

cheng_hoekstra_2013.tab5_pb_c2.software

Fonte: statsmodels 0.15.0: the reference specification of cheng_hoekstra_2013 tab5_pb_c2 (infer.ols, figure 'coef.cdl') on an independent code path
Tipo: software
Localização: cheng_hoekstra_2013: NBER Working Paper 18134, Table 5, Panel B 'Log Homicide Rate (OLS - Unweighted)', column (2) adding region-by-year fixed effects, row 'Castle Doctrine Law'
Valor: 0,08109020.08109024141547702 (se 0,08087020.08087017349667114)
Conferido por: execução de software · sm.OLS(l_homicide, add_constant(['cdl', 'r20001', 'r20002', 'r20003', 'r20004', 'r20011', 'r20012', 'r20013', 'r20014', 'r20021', 'r20022', 'r20023', 'r20024', 'r20031', 'r20032', 'r20033', 'r20034', 'r20041', 'r20042', 'r20043', 'r20044', 'r20051', 'r20052', 'r20053', 'r20054', 'r20061', 'r20062', 'r20063', 'r20064', 'r20071', 'r20072', 'r20073', 'r20074', 'r20081', 'r20082', 'r20083', 'r20084', 'r20091', 'r20092', 'r20093', 'r20094', 'r20101', 'r20102', 'r20103', 'r20104']), fe dummies ['sid', 'year']; 91 independent columns).fit(cov_type='cluster', groups=sid) on castle (the file pinned at sha256 804633c161827b6c0824f86f239046386d1a8266a866f83bf5ddb2aa762a5f29); n_obs = 550. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py.
Implementação: independente da ferramenta
Endereço: https://pypi.org/project/statsmodels/0.15.0/

#0 figura próxima: 0,08109020.08109024141547702 · relativa 0.000001 · absoluta 8.087017349667114e-8
#1 figura próxima: 0,08087020.08087017349667114 · relativa 0.000001 · absoluta 8.087017349667114e-8

cheng_hoekstra_2013.tab5_pb_c2.paper

Fonte: Cheng, C. and Hoekstra, M. (2013). Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine. Journal of Human Resources 48(3): 821-854. Cells read from the NBER Working Paper 18134 (June 2012).
Tipo: paper
Localização: NBER Working Paper 18134, Table 5 (the effect of castle doctrine on homicide), Panel B 'Log Homicide Rate (OLS - Unweighted)', column (2), row 'Castle Doctrine Law'
Página: 38
Trecho: Panel B: Castle Doctrine Law 0.0811 (0.0769)
Valor como publicado: 0.0811
Erro-padrão como publicado: 0.0769
Valor: 0,08110.0811 (se 0,07690.0769) log points of the homicide rate per unit of the castle doctrine law variable
Conferido por: fonte primária · Read on 2026-10-15 from the NBER Working Paper 18134 PDF (43 pages, created 2012-06-28) with pdftotext -layout and from the page image rendered at 80 dpi: Table 5 'The Effect of Castle Doctrine on Homicide' is on PDF page 40 (printed page 38). The published JHR version (48(3), 2013) could not be read without a subscription, so the cells are the authors' circulated working-paper version. The notes say 'Robust standard errors are clustered at the state level'; the unit is the state-year; 550 observations in every column. Panel A is weighted (by state population, 'OLS - Weighted'), Panel B unweighted. Column (1) has state and year fixed effects; column (2) adds region-by-year fixed effects.
sha256 da cópia lida: 1283a9c1e37ea2114e36b6c48ffc7c3fc0f26b2334f08c1a60ffbe82f3005682 (identifica a cópia lida, não um arquivo canônico)
Desvio conhecido: convenção de erro-padrão
Found in the software-reference run (scripts/paper_repro_reference.py, statsmodels 0.15.0, 2026-10-15), before the MAGI tool ran on this target: the declared specification (state, year and region-by-year effects as dummies, unweighted, CR1 clustered by state counting the dummies in K) gives an SE of 0.0809 against the printed 0.0769, the same ratio of about sqrt((N-k)/(N-K)) (k: the regressors left after absorbing the state effects, as Stata xtreg, fe counts them; K: the full dummy count) as Panel A, while the coefficient matches the printed one: the authors' clustered errors do not count the state effects, nested in the clusters, in K (Stata xtreg, fe). The reference keeps the declared convention; the printed cell is recorded and non-required on T1.
Endereço: https://www.nber.org/system/files/working_papers/w18134/w18134.pdf
Licença: NBER working paper, copyright the authors; cited, not reproduced.

#2 figura próxima: 0,08110.0811 · published_cell d=4 · absoluta 0.000050001000000000005
#3 figura próxima: 0,07690.0769 · published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#	Verificação	Obrigatória	Resultado	Esperado	Observado	Tolerância	Fonte	Chamada
0	figura próxima 0.08109024142 vs 0.08109024141547702	obrigatória	passou	0,0810902`0.08109024141547702`	0,0810902`0.08109024141548848`	relativa 0.000001 · absoluta 8.087017349667114e-8	cheng_hoekstra_2013.tab5_pb_c2.software	—
1	figura próxima 0.0808701735 vs 0.08087017349667114	obrigatória	passou	0,0808702`0.08087017349667114`	0,0808702`0.080870173496671`	relativa 0.000001 · absoluta 8.087017349667114e-8	cheng_hoekstra_2013.tab5_pb_c2.software	—
2	figura próxima 0.08109024142 vs 0.0811	obrigatória	passou	0,0811`0.0811`	0,0810902`0.08109024141548848`	published_cell d=4 · absoluta 0.000050001000000000005	cheng_hoekstra_2013.tab5_pb_c2.paper	—
3	figura próxima 0.0808701735 vs 0.0769	registrada	falhou	0,0769`0.0769`	0,0808702`0.080870173496671`	published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005	cheng_hoekstra_2013.tab5_pb_c2.paper	—

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

a própria especificação da tarefa

Referência: infer.olsChamada do agente: infer.ols (call_321f6cb7)igual

Argumentos da referência e do agente
Argumento	Referência	Agente
cluster	`"sid"`	`"sid"`	igual
controls	`["r20001","r20002","r20003","r20004","r20011","r20012","r20013","r20014","r20021","r20022","r20023","r20024","r20031","r20032","r20033","r20034","r20041","r20042","r20043","r20044","r20051","r20052","r20053","r20054","r20061","r20062","r20063","r20064","r20071","r20072","r20073","r20074","r20081","r20082","r20083","r20084","r20091","r20092","r20093","r20094","r20101","r20102","r20103","r20104"]`	`["r20001","r20002","r20003","r20004","r20011","r20012","r20013","r20014","r20021","r20022","r20023","r20024","r20031","r20032","r20033","r20034","r20041","r20042","r20043","r20044","r20051","r20052","r20053","r20054","r20061","r20062","r20063","r20064","r20071","r20072","r20073","r20074","r20081","r20082","r20083","r20084","r20091","r20092","r20093","r20094","r20101","r20102","r20103","r20104"]`	igual
dataset	`"castle"`	`"castle"`	igual
fe	`["sid","year"]`	`["sid","year"]`	igual
intercept	—	`true`	não fixado pela referência
level	—	0,95`0.95`	não fixado pela referência
se	—	`"HC1"`	não fixado pela referência
subset	—	—	não fixado pela referência
weights	—	—	igual
x	`["cdl"]`	`["cdl"]`	igual
y	`"l_homicide"`	`"l_homicide"`	igual

Trajetória

Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

0Início
Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.
castle (agent)
The state-year panel of Cheng and Hoekstra (2013), 'Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine', as distributed with Cunningham's Causal Inference: The Mixtape: one row per U.S. state and year, 2000-2010 (550 rows: 50 states, 11 years). Columns used most: state, the state's name; sid, a numeric state id; year; cdl, the castle doctrine law variable as the paper codes it: the fraction of the year in which the state's castle doctrine (stand-your-ground) law was in effect, 0 before adoption and 1 in full years after it; post, 1 in every year from the adoption year on (any part of the year); effyear and treatment_date, the year the law took effect (missing for states that never adopted one); homicide, the homicide rate per 100,000 residents (FBI Uniform Crime Reports), and l_homicide its natural log; murder and l_murder, the murder rate and its log; population; popwt, the state's average population over 2000-2010 (constant within a state), the weight the paper's weighted regressions use; northeast, midwest, south, west, census region indicators; r20001 to r20104, region-by-year indicators named r20<two-digit year><region 1-4> (for example r20063 is region 3 in 2006); trend_1 to trend_51, state-specific linear trends; lead1 to lead9 and lag0 to lag5, event-time indicators relative to adoption; other crime rates (robbery, assault, burglary, larceny, motor) and their logs (l_robbery and so on); and the time-varying controls of the paper (police, unemployrt, income, poverty, prisoner, lagprisoner, exp_subsidy, exp_pubwelfare, and the shares of black and white men aged 15-24 and 25-44).
file 804633c161827b6c0824f86f239046386d1a8266a866f83bf5ddb2aa762a5f29 · frame —

1Ferramenta

infer.olsv0.1.0call_321f6cb7decidido pelo códigoreexecutável

Argumentos

{
  "cluster": "sid",
  "controls": [
    "r20001",
    "r20002",
    "r20003",
    "r20004",
    "r20011",
    "r20012",
    "r20013",
    "r20014",
    "r20021",
    "r20022",
    "r20023",
    "r20024",
    "r20031",
    "r20032",
    "r20033",
    "r20034",
    "r20041",
    "r20042",
    "r20043",
    "r20044",
    "r20051",
    "r20052",
    "r20053",
    "r20054",
    "r20061",
    "r20062",
    "r20063",
    "r20064",
    "r20071",
    "r20072",
    "r20073",
    "r20074",
    "r20081",
    "r20082",
    "r20083",
    "r20084",
    "r20091",
    "r20092",
    "r20093",
    "r20094",
    "r20101",
    "r20102",
    "r20103",
    "r20104"
  ],
  "dataset": "castle",
  "fe": [
    "sid",
    "year"
  ],
  "intercept": true,
  "level": 0.95,
  "se": "HC1",
  "subset": null,
  "weights": null,
  "x": [
    "cdl"
  ],
  "y": "l_homicide"
}

Figuras call_321f6cb7
Chave	Valor	Valor bruto	Erro-padrão	IC
coef.cdl Coefficient on cdl in the regression of l_homicide	0,0810902	`0.08109024141548848`	0,0808702`0.080870173496671`	-0,0814245 – 0,243605

Diagnósticos

n_obs = 550550
k = 9191
r2 = 0,9152740.9152744967959459
df_resid = 459459
se_type = "cluster"
n_clusters = 5050
fixed_effects = "sid (50 levels), year (11 levels)"

Tabelas (1)

{
  "coefficients": [
    {
      "ci_high": 0.7741797803945534,
      "ci_low": 0.5797218136571007,
      "coef": 0.6769507970258271,
      "p": 9.694977976155178e-19,
      "se": 0.04838285303894466,
      "t": 13.99154358427212,
      "term": "Intercept"
    },
    {
      "ci_high": 0.24360493949674383,
      "ci_low": -0.08142445666576686,
      "coef": 0.08109024141548848,
      "p": 0.32092157860812803,
      "se": 0.080870173496671,
      "t": 1.00272124949536,
      "term": "cdl"
    },
    {
      "ci_high": 0.118011145029562,
      "ci_low": -0.30855797276126806,
      "coef": -0.09527341386585303,
      "p": 0.3737513155994151,
      "se": 0.10613414962263408,
      "t": -0.8976697340545243,
      "term": "r20001"
    },
    {
      "ci_high": 0.6670816915611157,
      "ci_low": 0.2010345409295885,
      "coef": 0.4340581162453521,
      "p": 0.0004775421302794401,
      "se": 0.11595663153604907,
      "t": 3.743279797761376,
      "term": "r20002"
    },
    {
      "ci_high": 1.4213196870434257,
      "ci_low": 1.190184556986409,
      "coef": 1.3057521220149173,
      "p": 1.1665835632193587e-27,
      "se": 0.05750845397239334,
      "t": 22.705394282408243,
      "term": "r20003"
    },
    {
      "ci_high": 0.30637527120200536,
      "ci_low": 0.0322601228866608,
      "coef": 0.16931769704433308,
      "p": 0.016517066877957055,
      "se": 0.06820226066950578,
      "t": 2.482581887788325,
      "term": "r20004"
    },
    {
      "ci_high": 0.06765009653479996,
      "ci_low": -0.26785042299557604,
      "coef": -0.10010016323038805,
      "p": 0.2362339851075746,
      "se": 0.08347548111949575,
      "t": -1.1991564695158083,
      "term": "r20011"
    },
    {
      "ci_high": 0.6070166406365023,
      "ci_low": 0.2459818522165092,
      "coef": 0.4264992464265057,
      "p": 0.00001825722150722625,
      "se": 0.08982863187937816,
      "t": 4.747920985807829,
      "term": "r20012"
    },
    {
      "ci_high": 1.4070434067325377,
      "ci_low": 1.1420847255514626,
      "coef": 1.2745640661420001,
      "p": 1.412026122565892e-24,
      "se": 0.065924051084442,
      "t": 19.33382498762725,
      "term": "r20013"
    },
    {
      "ci_high": 0.43897843151012084,
      "ci_low": 0.177128119799239,
      "coef": 0.30805327565467994,
      "p": 0.00001950725156523586,
      "se": 0.06515066141164881,
      "t": 4.7283215393359095,
      "term": "r20014"
    },
    {
      "ci_high": 0.05174083367412126,
      "ci_low": -0.29247248746198984,
      "coef": -0.12036582689393428,
      "p": 0.1662018533972377,
      "se": 0.08564330281752326,
      "t": -1.405431866054873,
      "term": "r20021"
    },
    {
      "ci_high": 0.5336806775097321,
      "ci_low": 0.2299203476704544,
      "coef": 0.3818005125900933,
      "p": 0.000006476895685771953,
      "se": 0.07557824266216871,
      "t": 5.051725194203365,
      "term": "r20022"
    },
    {
      "ci_high": 1.399785456828165,
      "ci_low": 1.1831573441112309,
      "coef": 1.2914714004696979,
      "p": 1.0336015332715826e-28,
      "se": 0.053898980419960864,
      "t": 23.960961606453996,
      "term": "r20023"
    },
    {
      "ci_high": 0.4429558712670536,
      "ci_low": 0.07928945777515542,
      "coef": 0.2611226645211045,
      "p": 0.005789786344785666,
      "se": 0.0904834033512999,
      "t": 2.8858625432920695,
      "term": "r20024"
    },
    {
      "ci_high": 0.08344780552353079,
      "ci_low": -0.23447674714641456,
      "coef": -0.07551447081144189,
      "p": 0.3444450108689908,
      "se": 0.07910242592462316,
      "t": -0.9546416551547958,
      "term": "r20031"
    },
    {
      "ci_high": 0.6111471986271204,
      "ci_low": 0.33902180114034774,
      "coef": 0.4750844998837341,
      "p": 6.2490647208954965e-9,
      "se": 0.06770719315677748,
      "t": 7.016750772457302,
      "term": "r20032"
    },
    {
      "ci_high": 1.4391957980628105,
      "ci_low": 1.199588314688986,
      "coef": 1.3193920563758983,
      "p": 3.667616970144512e-27,
      "se": 0.059616450020580816,
      "t": 22.13134220371084,
      "term": "r20033"
    },
    {
      "ci_high": 0.43777014470394027,
      "ci_low": 0.13057172016766602,
      "coef": 0.28417093243580316,
      "p": 0.0005164807718057423,
      "se": 0.07643367087243766,
      "t": 3.7178762866180293,
      "term": "r20034"
    },
    {
      "ci_high": 0.09609454540568925,
      "ci_low": -0.20363051086640432,
      "coef": -0.05376798273035753,
      "p": 0.4743359025099274,
      "se": 0.07457423109479173,
      "t": -0.7209994919292261,
      "term": "r20041"
    },
    {
      "ci_high": 0.5685816663812439,
      "ci_low": 0.31164652298398987,
      "coef": 0.44011409468261686,
      "p": 1.0013897728966103e-8,
      "se": 0.06392772428971019,
      "t": 6.884557515110195,
      "term": "r20042"
    },
    {
      "ci_high": 1.4006740268629754,
      "ci_low": 1.1847394760093275,
      "coef": 1.2927067514361514,
      "p": 8.561891917912833e-29,
      "se": 0.05372641612615587,
      "t": 24.060915367977007,
      "term": "r20043"
    },
    {
      "ci_high": 0.42160431421676065,
      "ci_low": 0.2081091797095755,
      "coef": 0.31485674696316807,
      "p": 3.0280344429585853e-7,
      "se": 0.053119467876249236,
      "t": 5.927332474351588,
      "term": "r20044"
    },
    {
      "ci_high": 0.0943593560277558,
      "ci_low": -0.1994759888252527,
      "coef": -0.05255831639874844,
      "p": 0.47561379983950036,
      "se": 0.0731088190738169,
      "t": -0.7189052848149698,
      "term": "r20051"
    },
    {
      "ci_high": 0.6719873551400278,
      "ci_low": 0.3579021665940566,
      "coef": 0.5149447608670422,
      "p": 2.8707492363980505e-8,
      "se": 0.07814715835040213,
      "t": 6.589424001293739,
      "term": "r20052"
    },
    {
      "ci_high": 1.445063134031174,
      "ci_low": 1.2253520015408967,
      "coef": 1.3352075677860353,
      "p": 4.3376033829343133e-29,
      "se": 0.054666062865141446,
      "t": 24.424798454571867,
      "term": "r20053"
    },
    {
      "ci_high": 0.41739033105442824,
      "ci_low": 0.10628789364818117,
      "coef": 0.2618391123513047,
      "p": 0.0014186564682126712,
      "se": 0.07740502362346723,
      "t": 3.382714714034681,
      "term": "r20054"
    },
    {
      "ci_high": 0.11016196921448385,
      "ci_low": -0.16348671738602927,
      "coef": -0.02666237408577271,
      "p": 0.6970536297865801,
      "se": 0.06808620089074931,
      "t": -0.3915973242295453,
      "term": "r20061"
    },
    {
      "ci_high": 0.6723726766144476,
      "ci_low": 0.3805925612343328,
      "coef": 0.5264826189243902,
      "p": 2.701823593770301e-9,
      "se": 0.07259745989827546,
      "t": 7.252080440033367,
      "term": "r20062"
    },
    {
      "ci_high": 1.442166314551658,
      "ci_low": 1.2120952656181379,
      "coef": 1.3271307900848979,
      "p": 4.572780476052481e-28,
      "se": 0.05724370122667967,
      "t": 23.183874586124066,
      "term": "r20063"
    },
    {
      "ci_high": 0.3893468041771025,
      "ci_low": 0.13633560061173194,
      "coef": 0.2628412023944172,
      "p": 0.00012165412145594965,
      "se": 0.06295141353523231,
      "t": 4.175302628388347,
      "term": "r20064"
    },
    {
      "ci_high": 0.02539108418662664,
      "ci_low": -0.318065864626471,
      "coef": -0.1463373902199222,
      "p": 0.0931366221847929,
      "se": 0.08545511072870804,
      "t": -1.7124474940357335,
      "term": "r20071"
    },
    {
      "ci_high": 0.6977117129505596,
      "ci_low": 0.3574045754877969,
      "coef": 0.5275581442191782,
      "p": 1.0312323954978334e-7,
      "se": 0.08467140995151429,
      "t": 6.230652643215412,
      "term": "r20072"
    },
    {
      "ci_high": 1.45820387582932,
      "ci_low": 1.1911874471354584,
      "coef": 1.3246956614823893,
      "p": 3.68202137559694e-25,
      "se": 0.06643603677046342,
      "t": 19.939414297984303,
      "term": "r20073"
    },
    {
      "ci_high": 0.5068324191228178,
      "ci_low": 0.1099741200433374,
      "coef": 0.3084032695830776,
      "p": 0.0030000175608350184,
      "se": 0.09874183652024117,
      "t": 3.1233292842376676,
      "term": "r20074"
    },
    {
      "ci_high": 0.17516612652454178,
      "ci_low": -0.16400891574221654,
      "coef": 0.005578605391162621,
      "p": 0.9475630053589809,
      "se": 0.08438973470614711,
      "t": 0.06610526043941059,
      "term": "r20081"
    },
    {
      "ci_high": 0.686473856403462,
      "ci_low": 0.2668050029788323,
      "coef": 0.4766394296911472,
      "p": 0.000033789231276185795,
      "se": 0.10441730313719032,
      "t": 4.564755221315254,
      "term": "r20082"
    },
    {
      "ci_high": 1.4507313978655172,
      "ci_low": 1.0876687919058896,
      "coef": 1.2692000948857034,
      "p": 8.220998543060823e-19,
      "se": 0.09033317072474421,
      "t": 14.050210843955707,
      "term": "r20083"
    },
    {
      "ci_high": 0.24745780240635537,
      "ci_low": 0.012716352789685942,
      "coef": 0.13008707759802066,
      "p": 0.030552816693657614,
      "se": 0.05840573800859709,
      "t": 2.2272996118784145,
      "term": "r20084"
    },
    {
      "ci_high": -0.016705013099140936,
      "ci_low": -0.3360398118052387,
      "coef": -0.1763724124521898,
      "p": 0.03108937005329756,
      "se": 0.07945330754629536,
      "t": -2.2198246731191427,
      "term": "r20091"
    },
    {
      "ci_high": 0.5601643765686921,
      "ci_low": 0.21708035078037075,
      "coef": 0.3886223636745314,
      "p": 0.00003518596641328553,
      "se": 0.085362324199026,
      "t": 4.55262163162804,
      "term": "r20092"
    },
    {
      "ci_high": 1.376907846926727,
      "ci_low": 1.0500016656759912,
      "coef": 1.2134547563013591,
      "p": 7.50967920295755e-20,
      "se": 0.08133713413928571,
      "t": 14.918828517161417,
      "term": "r20093"
    },
    {
      "ci_high": 0.22845537518368275,
      "ci_low": -0.04181015911817049,
      "coef": 0.09332260803275613,
      "p": 0.17147324863244395,
      "se": 0.0672444428325905,
      "t": 1.3878114547709013,
      "term": "r20094"
    },
    {
      "ci_high": 0.04508383156008358,
      "ci_low": -0.29887797860269316,
      "coef": -0.1268970735213048,
      "p": 0.144537443780071,
      "se": 0.0855807246744691,
      "t": -1.4827763378260037,
      "term": "r20101"
    },
    {
      "ci_high": 0.4691764266320758,
      "ci_low": 0.2279023805587597,
      "coef": 0.34853940359541774,
      "p": 4.651664789532676e-7,
      "se": 0.060031105483262716,
      "t": 5.805980096311804,
      "term": "r20102"
    },
    {
      "ci_high": 1.290561494522601,
      "ci_low": 0.9343903303445598,
      "coef": 1.1124759124335803,
      "p": 6.314878573873831e-17,
      "se": 0.08861851937597674,
      "t": 12.553537570558387,
      "term": "r20103"
    }
  ]
}

dropped as collinear with the other regressors: ['r20104', 'sid[46]', 'sid[50]', 'sid[51]', 'year[2001]', 'year[2002]', 'year[2003]', 'year[2004]', '…']

Digests dos dados: castle 6a9af2b4a14b985d82e0f3aea93c535c24cfc2497c4d9f07242bac5f84ae11c1
sha256 do resultado: ead83be5a62648f1371f6e969d2ab8dcdf45fec3ab7992c4ecd1d02349804cd8

2Pontuação
#0figura próximapassouobrigatória0.08109024142 vs 0.08109024141547702
3Pontuação
#1figura próximapassouobrigatória0.0808701735 vs 0.08087017349667114
4Pontuação
#2figura próximapassouobrigatória0.08109024142 vs 0.0811
5Pontuação
#3figura próximafalhouregistrada0.0808701735 vs 0.0769

Épocas × verificações

Resultado de cada verificação em cada época pontuada
#	0	1	2	3
Época 1	passou	passou	passou	falhou

Tentativas

Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

época 1, tentativa 1passoupontuada(exibindo)

Downloads desta tarefa

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Arquivo	Tamanho	sha256
sources/cheng_hoekstra_2013.tab5_pb_c2.paper.json	2,8 KB	`9b1869a00aedde618279754a39bfb9e7bcd6a0dab04a80739ee5f9432c8ca503`
sources/cheng_hoekstra_2013.tab5_pb_c2.software.json	1,7 KB	`48da04cb4a17bfc9a05abd26612a9e47a1361fb665e838c96f4e2dfe7976a194`
specs/paper_repro.cheng_hoekstra_2013.tab5_pb_c2.tool.json	6,9 KB	`545147846c15ba527398014a50fca14321c16bb25924dda7596cd9a9f7a429ad`
traces/paper_repro.cheng_hoekstra_2013.tab5_pb_c2.tool.e1.a1.jsonl	11,4 KB	`15506591e137de392cc62859d6a5c1c16d7619463eccc9613d206e9d2530a935`
trajectories/paper_repro.cheng_hoekstra_2013.tab5_pb_c2.tool.e1.a1.jsonl	16,2 KB	`e42e8645c0632b511aee4cd82ca81fddefc10aa03558e1aa06ece0938947aca6`