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Tarefa causcibench_real.q103

causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01d

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
1702.64807 vs 1592.937

Família do método (das chamadas de ferramentas): Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E) · infer.iv_2sls (iv · mínimos quadrados em dois estágios)

Calculado pelo agente
coef.JTPA training participation =1.702,651702.6480696896685
2SLS effect of JTPA training participation on income
via infer.iv_2sls (call_f2aa807c)
Valor esperado (gabarito)
coef.JTPA training participation =1.592,941592.937
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 103
Como foi validado
1 de 2 verificações obrigatórias aprovadas
relativa 0.05

Pergunta feita ao analista

What is the effect of receiving subsidized training on 30-month income of men?

Resposta

Estimativa (infer.iv_2sls): coef.JTPA training participation = 1703.

Como o agente resolveu e como foi validado

Resumo passo a passo do que o agente executou, por que o caminho está correto e como cada verificação conferiu o resultado.

  1. 1Preparação da base de dados
    abadie_instrumental_variables— This dataset was constructed to measure how subsidized Job Training Partnership Act (JTPA) programs affect not just average earnings but different points (quantiles) of the trainee earnings distribution. Data collection process: Data are drawn from the National JTPA Study - a large encouragement design randomized controlled trial under the JTPA. Eligible individuals were randomly assigned to be offered training services (treatment group) or excluded for 18 months (control group), with roughly 60% of those offered actually receiving training. Baseline demographic and economic covariates were collected before randomization, and earnings plus participation data were tracked for 30 months post-assignment via administrative records and follow-up interviews. Dataset variables: V1: Unique identifier for individuals income: Individual's income (continuous, ranges from 0 to ~155,760) JTPA training offer: Whether the person was offered JTPA training (binary: 1 = yes, 0 = no) JTPA training participation: Whether the person actually participated in JTPA training (binary) male: Gender (1 = male, 0 = female) hsorged: Completed high school or earned a GED (1 = yes, 0 = no) black: Race indicator (1 = Black, 0 = otherwise) hispanic: Ethnicity indicator (1 = Hispanic, 0 = otherwise) married: Marital status (1 = married, 0 = unmarried) wkless13: Employment status: whether worked less than 13 weeks in the year before program entry (1 = yes, 0 = no) afdc: Receipt of Aid to Families with Dependent Children (AFDC welfare program) (1 = yes, 0 = no) age2225: Age group indicator (22-25 years old) age2629: Age group indicator (26-29 years old) age3035: Age group indicator (30-35 years old) age3644: Age group indicator (36-44 years old) age4554: Age group indicator (45-54 years old) class_tr: Participation in classroom training (1 = yes, 0 = no) ojt_jsa: Participation in on-the-job training (OJT) or job search assistance (JSA) f2sms: Indicator for assignment to ""Follow-up survey sample"" or another experimental grouping
  2. 2Chamada que gerou a resposta finalinfer.iv_2sls(Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E))citada na respostacoincide com a referência
    Ver chamada call_f2aa807c nos detalhes

    causcibench_metadata_rule/1: iv

    Por que este é o caminho de referência: causcibench_metadata_rule/1: iv
    Argumentos principais
    dataset:
    "abadie_instrumental_variables"
    endog:
    ["JTPA training participation"]
    exog:
    ["hsorged","black","hispanic","married","wkless13","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"]
    instruments:
    ["JTPA training offer"]
    level:
    0,950.95
    se:
    "HC1"
    y:
    "income"
    Resultado calculado
    • coef.JTPA training participation = 1.702,65 1702.6480696896685
      2SLS effect of JTPA training participation on income
    Diagnósticos: first_stage_F.JTPA training participation = 11.272,911272.943843826715 (Wald F of the excluded instruments in the first stage for JTPA training participation (heteroskedasticity-robust standard errors (HC1))) · partial_r2.JTPA training participation = 0,3600870.3600868627355367 (share of the variation the instruments explain beyond the controls) · weak_instrument = false (every first-stage F is at least 10) · n_obs = 11.20411204 · se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
  3. 3Conferência de lastro e resposta final

    Todos os 1 números escritos na resposta foram conferidos contra as ferramentas e o enunciado (nenhum número sem lastro).

    Números encontrados: 1703
    Figuras citadas: call_f2aa807c:coef.JTPA training participation
    • #0resposta com lastro
      every number in the answer was stated by a tool call
    • #1figura da resposta próxima
      CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|

Aprofundamento técnico para especialistas

Acesso direto às fontes primárias, tabela formal de verificações, comparação de argumentos, trajetória completa com prompts brutos e somas SHA-256.

Valores esperados e de onde vêm

causcibench_real.gold.q103

Fonte
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 103
Tipo
benchmark_gold
Localização
real_input.json, record id 103: fields effect and std_error
Trecho
id 103 effect 1592.937 std_error 895.948
Valor como publicado
1592.937
Erro-padrão como publicado
895.948
Valor
1.592,941592.937 (se 895,948895.948)
Conferido por
arquivo do benchmark · Written by scripts/freeze_causcibench_real.py from the pinned file; equal to the `answer` and `std_error` of the same id in data/metadata_csv/real_input.csv at the pin.
sha256 da cópia lida
c1f4c8930675afff63d816d8ed066941ae92697e7bfc31e9d38519398dd80438 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://raw.githubusercontent.com/causalNLP/CauSciBench/d9bb43a2d90f261978cc5ac0b628c0484f6e8956/data/metadata_json/real_input.json
Licença
CauSciBench repository (MIT for code; metadata as published in the repository)
  • #1 figura da resposta próxima: 1.592,941592.937 · relativa 0.05
Especificação técnica do gabarito

CauSciBench real_input.json @ d9bb43a, id 103: effect 1592.937

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
0
resposta com lastro
every number in the answer was stated by a tool call
every number backed
obrigatóriapassou0 sem lastro0 sem lastro[]———
1
figura da resposta próxima
CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|
1702.64807 vs 1592.937
obrigatóriafalhou1.592,941592.9371.702,651702.6480696896685relativa 0.05causcibench_real.gold.q103call_f2aa807c

Caminho de referência e caminho do agente

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

caminho de referência do item · metadata_rule

Referência: infer.iv_2slsChamada do agente: infer.iv_2sls (call_f2aa807c)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"abadie_instrumental_variables""abadie_instrumental_variables"igual
endog["JTPA training participation"]["JTPA training participation"]igual
exog["hsorged","black","hispanic","married","wkless13","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"]["hsorged","black","hispanic","married","wkless13","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"]igual
instruments["JTPA training offer"]["JTPA training offer"]igual
level—0,950.95não fixado pela referência
se—"HC1"não fixado pela referência
subset——não fixado pela referência
y"income""income"igual

Trajetória

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

  1. 0Início

    What is the effect of receiving subsidized training on 30-month income of men?

    abadie_instrumental_variables (agent)

    This dataset was constructed to measure how subsidized Job Training Partnership Act (JTPA) programs affect not just average earnings but different points (quantiles) of the trainee earnings distribution. Data collection process: Data are drawn from the National JTPA Study - a large encouragement design randomized controlled trial under the JTPA. Eligible individuals were randomly assigned to be offered training services (treatment group) or excluded for 18 months (control group), with roughly 60% of those offered actually receiving training. Baseline demographic and economic covariates were collected before randomization, and earnings plus participation data were tracked for 30 months post-assignment via administrative records and follow-up interviews. Dataset variables: V1: Unique identifier for individuals income: Individual's income (continuous, ranges from 0 to ~155,760) JTPA training offer: Whether the person was offered JTPA training (binary: 1 = yes, 0 = no) JTPA training participation: Whether the person actually participated in JTPA training (binary) male: Gender (1 = male, 0 = female) hsorged: Completed high school or earned a GED (1 = yes, 0 = no) black: Race indicator (1 = Black, 0 = otherwise) hispanic: Ethnicity indicator (1 = Hispanic, 0 = otherwise) married: Marital status (1 = married, 0 = unmarried) wkless13: Employment status: whether worked less than 13 weeks in the year before program entry (1 = yes, 0 = no) afdc: Receipt of Aid to Families with Dependent Children (AFDC welfare program) (1 = yes, 0 = no) age2225: Age group indicator (22-25 years old) age2629: Age group indicator (26-29 years old) age3035: Age group indicator (30-35 years old) age3644: Age group indicator (36-44 years old) age4554: Age group indicator (45-54 years old) class_tr: Participation in classroom training (1 = yes, 0 = no) ojt_jsa: Participation in on-the-job training (OJT) or job search assistance (JSA) f2sms: Indicator for assignment to ""Follow-up survey sample"" or another experimental grouping

    file 07f3f196b42e8b021c7ed300807753a0c7ee104d9466807fc298890879e73c38 · frame —
  2. 1Turno do modelo
    call_941fbd93referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Texto visível

    causcibench_metadata_rule/1: iv

    Chamadas pedidas
    • infer.iv_2sls
      {
        "dataset": "abadie_instrumental_variables",
        "endog": [
          "JTPA training participation"
        ],
        "exog": [
          "hsorged",
          "black",
          "hispanic",
          "married",
          "wkless13",
          "class_tr",
          "ojt_jsa",
          "age2225",
          "age2629",
          "age3035",
          "age3644",
          "age4554",
          "f2sms"
        ],
        "instruments": [
          "JTPA training offer"
        ],
        "y": "income"
      }
  3. 2Ferramenta
    infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_f2aa807cdecidido pelo modeloreexecutável

    Motivo: causcibench_metadata_rule/1: iv

    Argumentos
    {
      "cluster": null,
      "dataset": "abadie_instrumental_variables",
      "endog": [
        "JTPA training participation"
      ],
      "exog": [
        "hsorged",
        "black",
        "hispanic",
        "married",
        "wkless13",
        "class_tr",
        "ojt_jsa",
        "age2225",
        "age2629",
        "age3035",
        "age3644",
        "age4554",
        "f2sms"
      ],
      "instruments": [
        "JTPA training offer"
      ],
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "y": "income"
    }
    Figuras call_f2aa807c
    ChaveValorValor brutoErro-padrãoIC
    coef.JTPA training participation
    2SLS effect of JTPA training participation on income
    1.702,651702.6480696896685503,552503.5516981474554715,598 – 2.689,7
    Diagnósticos
    • first_stage_F.JTPA training participation = 11.272,911272.943843826715 (Wald F of the excluded instruments in the first stage for JTPA training participation (heteroskedasticity-robust standard errors (HC1)))
    • partial_r2.JTPA training participation = 0,3600870.3600868627355367 (share of the variation the instruments explain beyond the controls)
    • weak_instrument = false (every first-stage F is at least 10)
    • n_obs = 11.20411204
    • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
    • n_clusters = — (errors not clustered)
    Derivação matemática e pressupostos
    coef.JTPA training participation
    1. Com um instrumento e um regressor endógeno, o MQ2E é a razão entre o coeficiente de JTPA training offer na forma reduzida (income sobre JTPA training offer e os controles) e no primeiro estágio (JTPA training participation sobre JTPA training offer e os controles).β = ρ / π→ 1.702,65 (1702.6480696896685)
    2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 503,552 (503.5516981474554)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 11189 graus de liberdade vezes o erro-padrão.IC = β ± c · ep
    Pressupostos do estimador
    • the instruments affect the outcome only through the endogenous regressors (exclusion restriction)
    • the instruments are as good as randomly assigned given the controls
    • errors are independent across observations; their variance may differ
    Tabelas (3)
    {
      "coefficients": [
        {
          "ci_high": 12611.997071626314,
          "ci_low": 9440.113047230998,
          "coef": 11026.055059428656,
          "p": 5.908534897288086e-42,
          "se": 809.0814252230848,
          "t": 13.627868241306473,
          "term": "Intercept"
        },
        {
          "ci_high": 4352.359414880281,
          "ci_low": 3061.204487620525,
          "coef": 3706.781951250403,
          "p": 3.142674231390705e-29,
          "se": 329.3466787236278,
          "t": 11.254954704920403,
          "term": "hsorged"
        },
        {
          "ci_high": -701.3539219581587,
          "ci_low": -2097.8700815005386,
          "coef": -1399.6120017293485,
          "p": 0.00008579744380681868,
          "se": 356.2221304497472,
          "t": -3.929042813713658,
          "term": "black"
        },
        {
          "ci_high": 161.17235312981416,
          "ci_low": -1712.2115329459505,
          "coef": -775.5195899080682,
          "p": 0.10463951393187298,
          "se": 477.86113643455036,
          "t": -1.6228973875013712,
          "term": "hispanic"
        },
        {
          "ci_high": 5078.301042312055,
          "ci_low": 3513.9894093083217,
          "coef": 4296.145225810188,
          "p": 6.699311187161305e-27,
          "se": 399.023254251862,
          "t": 10.766653772761016,
          "term": "married"
        },
        {
          "ci_high": -6516.594286697176,
          "ci_low": -7789.515153755572,
          "coef": -7153.054720226374,
          "p": 2.5255647024414334e-105,
          "se": 324.6955504661458,
          "t": -22.030036167595046,
          "term": "wkless13"
        },
        {
          "ci_high": -1724.1368954512845,
          "ci_low": -3276.6149176379477,
          "coef": -2500.375906544616,
          "p": 2.822070779154482e-10,
          "se": 396.0047470707126,
          "t": -6.314004882618582,
          "term": "class_tr"
        },
        {
          "ci_high": 1833.1561868821295,
          "ci_low": 303.7285348799022,
          "coef": 1068.442360881016,
          "p": 0.006177697086844569,
          "se": 390.12507864106436,
          "t": 2.7387174508307868,
          "term": "ojt_jsa"
        },
        {
          "ci_high": 5543.648442983713,
          "ci_low": 2679.3337054212593,
          "coef": 4111.491074202486,
          "p": 1.874025692790611e-8,
          "se": 730.6269183648081,
          "t": 5.627346831682957,
          "term": "age2225"
        },
        {
          "ci_high": 6014.982222081624,
          "ci_low": 3097.1801464352934,
          "coef": 4556.081184258459,
          "p": 9.57806099192944e-10,
          "se": 744.2704221611183,
          "t": 6.121540032491264,
          "term": "age2629"
        },
        {
          "ci_high": 5791.338294509802,
          "ci_low": 2907.95969429423,
          "coef": 4349.648994402016,
          "p": 3.4376519840728547e-9,
          "se": 735.489711911802,
          "t": 5.913949473332149,
          "term": "age3035"
        },
        {
          "ci_high": 5305.758490320646,
          "ci_low": 2366.7238852148016,
          "coef": 3836.241187767724,
          "p": 3.153678918989525e-7,
          "se": 749.6863973556935,
          "t": 5.117127910148802,
          "term": "age3644"
        },
        {
          "ci_high": 3524.4039598184254,
          "ci_low": 324.32721489610367,
          "coef": 1924.3655873572645,
          "p": 0.01841542577335949,
          "se": 816.2727999169481,
          "t": 2.357503015600985,
          "term": "age4554"
        },
        {
          "ci_high": 2178.9603252458496,
          "ci_low": 886.229651709843,
          "coef": 1532.5949884778463,
          "p": 0.000003393803095882883,
          "se": 329.74861871675915,
          "t": 4.647767728162294,
          "term": "f2sms"
        },
        {
          "ci_high": 2689.6980358724013,
          "ci_low": 715.5981035069357,
          "coef": 1702.6480696896685,
          "p": 0.0007239653280671672,
          "se": 503.5516981474554,
          "t": 3.381277584712029,
          "term": "JTPA training participation"
        }
      ],
      "first_stage": [
        {
          "ci_high": 0.6372441125397917,
          "ci_low": 0.6141411623590348,
          "coef": 0.6256926374494133,
          "endog": "JTPA training participation",
          "instrument": "JTPA training offer",
          "p": 0,
          "se": 0.005893080489494922,
          "t": 106.17412040524148
        }
      ],
      "reduced_form": [
        {
          "ci_high": 1683.7279548303702,
          "ci_low": 446.94076791419343,
          "coef": 1065.3343613722818,
          "instrument": "JTPA training offer",
          "p": 0.0007356188637250442,
          "se": 315.4786026826926,
          "t": 3.376883098609993
        }
      ]
    }
    Hashes SHA-256 e metadados de reprodução
    Digests dos dados
    abadie_instrumental_variables 7d1e5077d40b12f4726ea5b1690837de3f5067be68b661660c27c9d21475aa9d
    sha256 do resultado
    83244715339076d7680413a2c78d5bbdffbf2623a96417a88f9e359599a6f6e4
  4. 3Turno do modelo
    call_e6bf3a78referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Chamadas pedidas
    • submit_answer (meta-ferramenta)
      {
        "answer": "Estimativa (infer.iv_2sls): coef.JTPA training participation = 1703.",
        "caveats": [],
        "figure_refs": [
          "call_f2aa807c:coef.JTPA training participation"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    1703
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.iv_2sls): coef.JTPA training participation = 1703.

    Figuras citadas: call_f2aa807c:coef.JTPA training participation · Parada: answered
    Figura da resposta: call_f2aa807c:coef.JTPA training participation = 1.702,651702.6480696896685 (se 503,552503.5516981474554)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta próximafalhouobrigatória1702.64807 vs 1592.937

Épocas × verificações

Resultado de cada verificação em cada época pontuada
#01
Época 1passoufalhou

Tentativas

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

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