Pular para o conteúdo

Tarefa causcibench_real.q078

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

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
0.003853649487 vs -0.018

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.contacted_3days =0,003853650.003853649486872875
2SLS effect of contacted_3days on vtr_gen05
via infer.iv_2sls (call_3e2dc1b6)
Valor esperado (gabarito)
coef.contacted_3days =-0,018-0.018
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 78
Como foi validado
1 de 2 verificações obrigatórias aprovadas
relativa 0.05

Pergunta feita ao analista

Among high-propensity voters, defined as those with a voting propensity greater than 0.68, what is the effect of receiving a get-out-the-vote phone call three days prior to the election on turnout?

Resposta

Estimativa (infer.iv_2sls): coef.contacted_3days = 0,003854.

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
    panagopoulos_timing— The dataset consists of 25,000 registered voters in Rochester, New York, who were part of a randomized field experiment during the November 2005 municipal elections. Voters were randomly assigned to one of four groups: a phone reminder call scheduled for 4 weeks before Election Day, 2 weeks before, 3 days before, or a control group that received no call. The calls were nonpartisan get-out-the-vote reminders, delivered using standardized scripts. The unit of observation is the individual registered voter, and only those appearing on the official registration list were included. The main outcome is voter turnout in the 2005 election, while additional measures capture past voting history, party registration, demographics, and a predicted propensity to vote. The dataset also records whether each assigned reminder call was actually completed, allowing for comparison between group assignment and the reality of who was contacted. Data variables: vtr_gen01: Voted (2001) vtr_gen03: Voted (2003) vtr_gen05: Outcome: Voted 2005 treated: Successfully contacted four_weeks: Experimental group: Called 4 weeks before election two_weeks: Experimental group: Called 2 weeks before election three_days: Experimental group: Called 3 days before election control: Experimental group: Control, i.e., did not receive any calls democrat: Registered Democrat republican: Registered Republican unenrolled: Unaffiliated other_party: Other party registration age: Age (years) age_squared: Age squared contacted_4weeks: Successfully contacted: 4 weeks contacted_2weeks: Successfully contacted: 2 weeks contacted_3days: Successfully contacted: 3 days vote_prop: Predicted vote propensity use: Subject included id: Subject ID
  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_3e2dc1b6 nos detalhes

    causcibench_metadata_rule/1: iv

    Por que este é o caminho de referência: causcibench_metadata_rule/1: iv
    Argumentos principais
    dataset:
    "panagopoulos_timing"
    endog:
    ["contacted_3days"]
    exog:
    ["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]
    instruments:
    ["three_days"]
    level:
    0,950.95
    se:
    "HC1"
    y:
    "vtr_gen05"
    Resultado calculado
    • coef.contacted_3days = 0,00385365 0.003853649486872875
      2SLS effect of contacted_3days on vtr_gen05
    Diagnósticos: first_stage_F.contacted_3days = 2.033,222033.2184432232875 (Wald F of the excluded instruments in the first stage for contacted_3days (heteroskedasticity-robust standard errors (HC1))) · partial_r2.contacted_3days = 0,4912030.49120252933552255 (share of the variation the instruments explain beyond the controls) · weak_instrument = false (every first-stage F is at least 10) · n_obs = 24.17124171 · 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: 0,003854
    Figuras citadas: call_3e2dc1b6:coef.contacted_3days
    • #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.q078

Fonte
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 78
Tipo
benchmark_gold
Localização
real_input.json, record id 78: fields effect and std_error
Trecho
id 78 effect -0.018 std_error 0.023
Valor como publicado
-0.018
Erro-padrão como publicado
0.023
Valor
-0,018-0.018 (se 0,0230.023)
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: -0,018-0.018 · relativa 0.05
Especificação técnica do gabarito

CauSciBench real_input.json @ d9bb43a, id 78: effect -0.018

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|
0.003853649487 vs -0.018
obrigatóriafalhou-0,018-0.0180,003853650.003853649486872875relativa 0.05causcibench_real.gold.q078call_3e2dc1b6

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_3e2dc1b6)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"panagopoulos_timing""panagopoulos_timing"igual
endog["contacted_3days"]["contacted_3days"]igual
exog["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]igual
instruments["three_days"]["three_days"]igual
level—0,950.95não fixado pela referência
se—"HC1"não fixado pela referência
subset——não fixado pela referência
y"vtr_gen05""vtr_gen05"igual

Pendências do caminho de referência: needs_spec:sample, needs_spec:subgroup

Trajetória

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

  1. 0Início

    Among high-propensity voters, defined as those with a voting propensity greater than 0.68, what is the effect of receiving a get-out-the-vote phone call three days prior to the election on turnout?

    panagopoulos_timing (agent)

    The dataset consists of 25,000 registered voters in Rochester, New York, who were part of a randomized field experiment during the November 2005 municipal elections. Voters were randomly assigned to one of four groups: a phone reminder call scheduled for 4 weeks before Election Day, 2 weeks before, 3 days before, or a control group that received no call. The calls were nonpartisan get-out-the-vote reminders, delivered using standardized scripts. The unit of observation is the individual registered voter, and only those appearing on the official registration list were included. The main outcome is voter turnout in the 2005 election, while additional measures capture past voting history, party registration, demographics, and a predicted propensity to vote. The dataset also records whether each assigned reminder call was actually completed, allowing for comparison between group assignment and the reality of who was contacted. Data variables: vtr_gen01: Voted (2001) vtr_gen03: Voted (2003) vtr_gen05: Outcome: Voted 2005 treated: Successfully contacted four_weeks: Experimental group: Called 4 weeks before election two_weeks: Experimental group: Called 2 weeks before election three_days: Experimental group: Called 3 days before election control: Experimental group: Control, i.e., did not receive any calls democrat: Registered Democrat republican: Registered Republican unenrolled: Unaffiliated other_party: Other party registration age: Age (years) age_squared: Age squared contacted_4weeks: Successfully contacted: 4 weeks contacted_2weeks: Successfully contacted: 2 weeks contacted_3days: Successfully contacted: 3 days vote_prop: Predicted vote propensity use: Subject included id: Subject ID

    file 37ac4466ad26ac40012073e833298d7e3f2f8e8fbe8eb1fa90268ec2e1181ad7 · frame —
  2. 1Turno do modelo
    call_9cb8342creferenceFim: 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": "panagopoulos_timing",
        "endog": [
          "contacted_3days"
        ],
        "exog": [
          "democrat",
          "republican",
          "unenrolled",
          "other_party",
          "age",
          "age_squared",
          "vtr_gen01",
          "vtr_gen03"
        ],
        "instruments": [
          "three_days"
        ],
        "y": "vtr_gen05"
      }
  3. 2Ferramenta
    infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_3e2dc1b6decidido pelo modeloreexecutável

    Motivo: causcibench_metadata_rule/1: iv

    Argumentos
    {
      "cluster": null,
      "dataset": "panagopoulos_timing",
      "endog": [
        "contacted_3days"
      ],
      "exog": [
        "democrat",
        "republican",
        "unenrolled",
        "other_party",
        "age",
        "age_squared",
        "vtr_gen01",
        "vtr_gen03"
      ],
      "instruments": [
        "three_days"
      ],
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "y": "vtr_gen05"
    }
    Figuras call_3e2dc1b6
    ChaveValorValor brutoErro-padrãoIC
    coef.contacted_3days
    2SLS effect of contacted_3days on vtr_gen05
    0,003853650.0038536494868728750,01901380.019013830982771096-0,0334146 – 0,0411219
    Diagnósticos
    • first_stage_F.contacted_3days = 2.033,222033.2184432232875 (Wald F of the excluded instruments in the first stage for contacted_3days (heteroskedasticity-robust standard errors (HC1)))
    • partial_r2.contacted_3days = 0,4912030.49120252933552255 (share of the variation the instruments explain beyond the controls)
    • weak_instrument = false (every first-stage F is at least 10)
    • n_obs = 24.17124171
    • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
    • n_clusters = — (errors not clustered)
    Derivação matemática e pressupostos
    coef.contacted_3days
    1. Com um instrumento e um regressor endógeno, o MQ2E é a razão entre o coeficiente de three_days na forma reduzida (vtr_gen05 sobre three_days e os controles) e no primeiro estágio (contacted_3days sobre three_days e os controles).β = ρ / π→ 0,00385365 (0.003853649486872875)
    2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0190138 (0.019013830982771096)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 24161 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": 0.028092743705918244,
          "ci_low": -0.040881112090955324,
          "coef": -0.006394184192518538,
          "p": 0.7162995574914452,
          "se": 0.017594813232062054,
          "t": -0.36341301883595845,
          "term": "Intercept"
        },
        {
          "ci_high": 0.04870457254181071,
          "ci_low": -0.012073768166990111,
          "coef": 0.018315402187410297,
          "p": 0.23748735301743137,
          "se": 0.015504186926642098,
          "t": 1.1813197476313615,
          "term": "democrat"
        },
        {
          "ci_high": 0.011270086571664832,
          "ci_low": -0.05032984096926176,
          "coef": -0.019529877198798465,
          "p": 0.21393471264675448,
          "se": 0.015713768755846284,
          "t": -1.2428512537154655,
          "term": "republican"
        },
        {
          "ci_high": -0.00041415233665221055,
          "ci_low": -0.0624043045281415,
          "coef": -0.03140922843239685,
          "p": 0.047016598115522126,
          "se": 0.015813312702837114,
          "t": -1.986252281393362,
          "term": "unenrolled"
        },
        {
          "ci_high": 0.02601963962381732,
          "ci_low": -0.04560091604241428,
          "coef": -0.009790638209298477,
          "p": 0.5920416352982516,
          "se": 0.018269970352751665,
          "t": -0.5358869237477386,
          "term": "other_party"
        },
        {
          "ci_high": 0.0050561567546655905,
          "ci_low": 0.003659109174918845,
          "coef": 0.004357632964792218,
          "p": 2.797768893590162e-34,
          "se": 0.0003563783836347816,
          "t": 12.227545678690607,
          "term": "age"
        },
        {
          "ci_high": -0.00001650586663948991,
          "ci_low": -0.000024960199592835418,
          "coef": -0.000020733033116162664,
          "p": 7.670226566055696e-22,
          "se": 0.0000021566491766656374,
          "t": -9.613539995511784,
          "term": "age_squared"
        },
        {
          "ci_high": 0.30513638924338915,
          "ci_low": 0.27571793802256817,
          "coef": 0.29042716363297866,
          "p": 0,
          "se": 0.007504468886460809,
          "t": 38.700562028707054,
          "term": "vtr_gen01"
        },
        {
          "ci_high": 0.3543955460942047,
          "ci_low": 0.3253037388507081,
          "coef": 0.3398496424724564,
          "p": 0,
          "se": 0.0074211439844671405,
          "t": 45.794778161396714,
          "term": "vtr_gen03"
        },
        {
          "ci_high": 0.041121940404618584,
          "ci_low": -0.03341464143087283,
          "coef": 0.003853649486872875,
          "p": 0.8393898959835998,
          "se": 0.019013830982771096,
          "t": 0.2026761198395401,
          "term": "contacted_3days"
        }
      ],
      "first_stage": [
        {
          "ci_high": 0.5332636032310409,
          "ci_low": 0.48883421935432536,
          "coef": 0.5110489112926832,
          "endog": "contacted_3days",
          "instrument": "three_days",
          "p": 0,
          "se": 0.011333666971273403,
          "t": 45.091223572035474
        }
      ],
      "reduced_form": [
        {
          "ci_high": 0.021020018970740448,
          "ci_low": -0.017081212221200487,
          "coef": 0.001969403374769979,
          "instrument": "three_days",
          "p": 0.8394289484183484,
          "se": 0.00971939351495853,
          "t": 0.20262615889962574
        }
      ]
    }
    • 829 rows were dropped because one of 'vtr_gen05', 'contacted_3days', 'three_days', 'democrat', 'republican', 'unenrolled', 'other_party', 'age', 'age_squared', 'vtr_gen01', 'vtr_gen03' was missing
    Hashes SHA-256 e metadados de reprodução
    Digests dos dados
    panagopoulos_timing a9840be060a94f8bcf5d9657e12a817f7e5a23d132aea3f8161124cbc615d87e
    sha256 do resultado
    83dd4472087f19b0b5f37aefb10c147bbe71e60726a35043ac5b7c879221be0c
  4. 3Turno do modelo
    call_9b0e180dreferenceFim: 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.contacted_3days = 0,003854.",
        "caveats": [],
        "figure_refs": [
          "call_3e2dc1b6:coef.contacted_3days"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    0,003854
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.iv_2sls): coef.contacted_3days = 0,003854.

    Figuras citadas: call_3e2dc1b6:coef.contacted_3days · Parada: answered
    Figura da resposta: call_3e2dc1b6:coef.contacted_3days = 0,003853650.003853649486872875 (se 0,01901380.019013830982771096)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta próximafalhouobrigatória0.003853649487 vs -0.018

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.

Downloads desta tarefa

Pacote da tarefa (.zip)
101,8 KB · sha256 f450bc5494f247e45f8fa233c8c686474d7ba54921d4c8dc2eed99bf57f48d06

O hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.

Downloads desta tarefa
ArquivoTamanhosha256
attachments/3b981acfe973d86a5c600e306dc05042b2bb3721e1e750b765d2bad843c0ab02.json336 B3b981acfe973d86a5c600e306dc05042b2bb3721e1e750b765d2bad843c0ab02
attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json2,4 KB433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420
attachments/52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b.json64,0 KB52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b
attachments/594c81688cad881d3135d3ed5cad9d6d66b1786f139892fbd345d3879320d58a.json222 B594c81688cad881d3135d3ed5cad9d6d66b1786f139892fbd345d3879320d58a
attachments/7b3fcdc38051078d800f8ac2314d8764e0862cd7fed2975749ab5f608bcf0ee0.json2,5 KB7b3fcdc38051078d800f8ac2314d8764e0862cd7fed2975749ab5f608bcf0ee0
attachments/7b5b5e76084bc7f66e87b7e2f4af72275587eb3029beed7374f9c81f995faaef.json2,7 KB7b5b5e76084bc7f66e87b7e2f4af72275587eb3029beed7374f9c81f995faaef
attachments/9307369b4d189cecc2674c3b2075aedf580c2722db42da9881b9d58566b2d50d.json2,5 KB9307369b4d189cecc2674c3b2075aedf580c2722db42da9881b9d58566b2d50d
native/causcibench_real/causcibench_real.q078.e1.a1.json2,0 KB001b2f814a404660294b7592b20c4ec5052fc64491761124d317acfe6e09ce82
sources/causcibench_real.gold.q078.json1,2 KB39abdfe53fbda61d55ca71851e648a3958998cc926ffd29f8eef8d2dfb10c5ed
specs/causcibench_real.q078.json6,5 KBb2f2fd2d513275aaa7cfb4ab415cbe0a489f038b4e77cd031cf6704a987cd9fa
traces/causcibench_real.q078.e1.a1.jsonl16,3 KB0cf214237e3bdd60c62826fc2332bb113a9a987359d9bacf2b844a7b672c7374
trajectories/causcibench_real.q078.e1.a1.jsonl13,1 KB15f09eec4d92277aa98b083407c58c35f8413aaa2e0b2675f2318e711eb30c53