Tarefa causcibench_real.q104
causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01dVeredito
1679.259893 vs 1779.922Família do método (das chamadas de ferramentas): Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E) · infer.iv_2sls (iv · mínimos quadrados em dois estágios)
coef.JTPA training participation =1.679,261679.2598927825413coef.JTPA training participation =1.779,921779.922Pergunta feita ao analista
What is the effect of receiving subsidized training on 30-month income of women?
Estimativa (infer.iv_2sls): coef.JTPA training participation = 1679.
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.
- 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 - 2Chamada que gerou a resposta finalVer chamada call_952ea94c nos detalhes
infer.iv_2sls(Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E))citada na respostacoincide com a referênciacauscibench_metadata_rule/1: iv
Por que este é o caminho de referência: causcibench_metadata_rule/1: ivArgumentos principais- dataset:
"abadie_instrumental_variables"- endog:
["JTPA training participation"]- exog:
["hsorged","black","hispanic","married","wkless13","afdc","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"]- instruments:
["JTPA training offer"]- level:
- 0,95
0.95 - se:
"HC1"- y:
"income"
Resultado calculadocoef.JTPA training participation= 1.679,261679.25989278254132SLS effect of JTPA training participation on income
Diagnósticos:first_stage_F.JTPA training participation= 11.283,811283.763800105484(Wald F of the excluded instruments in the first stage for JTPA training participation (heteroskedasticity-robust standard errors (HC1))) ·partial_r2.JTPA training participation= 0,3602570.3602568868328082(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)) - 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:1679Figuras citadas:call_952ea94c:coef.JTPA training participation- #0resposta com lastroevery number in the answer was stated by a tool call
- #1figura da resposta próximaCauSciBench 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.q104
- Fonte
- CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 104
- Tipo
- benchmark_gold
- Localização
- real_input.json, record id 104: fields effect and std_error
- Trecho
id 104 effect 1779.922 std_error 532.367
- Valor como publicado
1779.922- Erro-padrão como publicado
532.367- Valor
- 1.779,92
1779.922(se 532,367532.367) - 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: 1.779,92
1779.922· relativa 0.05
Especificação técnica do gabarito
CauSciBench real_input.json @ d9bb43a, id 104: effect 1779.922
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number in the answer was stated by a tool call every number backed | obrigatória | passou | 0 sem lastro | 0 sem lastro[] | — | — | — |
| 1 | figura da resposta próxima CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold| 1679.259893 vs 1779.922 | obrigatória | falhou | 1.779,921779.922 | 1.679,261679.2598927825413 | relativa 0.05 | causcibench_real.gold.q104 | call_952ea94c |
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
| Argumento | Referência | Agente | |
|---|---|---|---|
| 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","afdc","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"] | ["hsorged","black","hispanic","married","wkless13","afdc","class_tr","ojt_jsa","age2225","age2629","age3035","age3644","age4554","f2sms"] | igual |
| instruments | ["JTPA training offer"] | ["JTPA training offer"] | igual |
| level | — | 0,950.95 | não 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.
- 0Início
What is the effect of receiving subsidized training on 30-month income of women?
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
file07f3f196b42e8b021c7ed300807753a0c7ee104d9466807fc298890879e73c38· frame — - 1Turno do modelo
call_055260c9referenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelcauscibench_metadata_rule/1: iv
Chamadas pedidasinfer.iv_2sls{ "dataset": "abadie_instrumental_variables", "endog": [ "JTPA training participation" ], "exog": [ "hsorged", "black", "hispanic", "married", "wkless13", "afdc", "class_tr", "ojt_jsa", "age2225", "age2629", "age3035", "age3644", "age4554", "f2sms" ], "instruments": [ "JTPA training offer" ], "y": "income" }
- 2Ferramenta
infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_952ea94cdecidido pelo modeloreexecutávelMotivo: causcibench_metadata_rule/1: iv
Argumentos
{ "cluster": null, "dataset": "abadie_instrumental_variables", "endog": [ "JTPA training participation" ], "exog": [ "hsorged", "black", "hispanic", "married", "wkless13", "afdc", "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_952ea94c Chave Valor Valor bruto Erro-padrão IC coef.JTPA training participation 2SLS effect of JTPA training participation on income1.679,26 1679.2598927825413501,612 501.61212543563096696,012 – 2.662,51 Diagnósticosfirst_stage_F.JTPA training participation= 11.283,811283.763800105484(Wald F of the excluded instruments in the first stage for JTPA training participation (heteroskedasticity-robust standard errors (HC1)))partial_r2.JTPA training participation= 0,3602570.3602568868328082(share of the variation the instruments explain beyond the controls)weak_instrument=false(every first-stage F is at least 10)n_obs= 11.20411204se_type="HC1"(heteroskedasticity-robust standard errors (HC1))n_clusters= — (errors not clustered)
Derivação matemática e pressupostos
coef.JTPA training participation- 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→ 1.679,26 (1679.2598927825413) - Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.
ep = √V_jj→ 501,612 (501.61212543563096) - Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 11188 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": 12371.325021322753, "ci_low": 9200.071448363453, "coef": 10785.698234843103, "p": 2.9985492228571027e-40, "se": 808.9206023956164, "t": 13.33344484353753, "term": "Intercept" }, { "ci_high": 4211.908628585577, "ci_low": 2922.1476986760636, "coef": 3567.0281636308205, "p": 2.962627353048922e-27, "se": 328.99109590758815, "t": 10.842324330360539, "term": "hsorged" }, { "ci_high": -379.4997471380227, "ci_low": -1780.07443706855, "coef": -1079.7870921032863, "p": 0.0025131758400244114, "se": 357.2573734056291, "t": -3.0224347276866386, "term": "black" }, { "ci_high": 349.4224355662774, "ci_low": -1517.2544209299485, "coef": -583.9159926818355, "p": 0.22010144344590066, "se": 476.1503085437004, "t": -1.226327027840715, "term": "hispanic" }, { "ci_high": 4779.151040115989, "ci_low": 3209.6935735513644, "coef": 3994.422306833677, "p": 2.3894116039197575e-23, "se": 400.33584514121367, "t": 9.977678380072842, "term": "married" }, { "ci_high": -5886.138327172579, "ci_low": -7184.985358081125, "coef": -6535.561842626852, "p": 3.547818305834217e-85, "se": 331.3087706455014, "t": -19.726498124071302, "term": "wkless13" }, { "ci_high": -2905.4402633793766, "ci_low": -4274.1074565590925, "coef": -3589.7738599692348, "p": 1.089422506605359e-24, "se": 349.118436893997, "t": -10.282395544349894, "term": "afdc" }, { "ci_high": -1298.0269503192237, "ci_low": -2862.858301964813, "coef": -2080.4426261420185, "p": 1.9003480922825395e-7, "se": 399.15581977239225, "t": -5.212106458395958, "term": "class_tr" }, { "ci_high": 1816.8380785446993, "ci_low": 290.4004702217202, "coef": 1053.6192743832098, "p": 0.006819980843845018, "se": 389.36237712826875, "t": 2.7060120244645853, "term": "ojt_jsa" }, { "ci_high": 6227.493906616717, "ci_low": 3342.8186999241734, "coef": 4785.156303270445, "p": 8.20031017316732e-11, "se": 735.8204420518538, "t": 6.503157604492364, "term": "age2225" }, { "ci_high": 6734.474828257452, "ci_low": 3791.734172686177, "coef": 5263.104500471814, "p": 2.4924310876712566e-12, "se": 750.6317262348225, "t": 7.011566813025087, "term": "age2629" }, { "ci_high": 6474.374630775145, "ci_low": 3568.146485708311, "coef": 5021.260558241728, "p": 1.3207905199682341e-11, "se": 741.3181468212825, "t": 6.773421883401239, "term": "age3035" }, { "ci_high": 5791.919824155861, "ci_low": 2840.386243277124, "coef": 4316.153033716492, "p": 1.0128316971853773e-8, "se": 752.8746179723928, "t": 5.732897524611145, "term": "age3644" }, { "ci_high": 3860.451978176201, "ci_low": 654.165613926313, "coef": 2257.308796051257, "p": 0.005789018989810076, "se": 817.8567363194447, "t": 2.7600295941923747, "term": "age4554" }, { "ci_high": 2200.5761535014253, "ci_low": 913.3553955018799, "coef": 1556.9657745016527, "p": 0.0000021435187410712202, "se": 328.34315106674643, "t": 4.741885949023949, "term": "f2sms" }, { "ci_high": 2662.507964544147, "ci_low": 696.0118210209356, "coef": 1679.2598927825413, "p": 0.0008174628223406107, "se": 501.61212543563096, "t": 3.3477258774878464, "term": "JTPA training participation" } ], "first_stage": [ { "ci_high": 0.637334596630317, "ci_low": 0.6142392458991346, "coef": 0.6257869212647258, "endog": "JTPA training participation", "instrument": "JTPA training offer", "p": 0, "se": 0.0058911419715240625, "t": 106.22506201507008 } ], "reduced_form": [ { "ci_high": 1667.0008149917826, "ci_low": 434.71694162366157, "coef": 1050.858878307722, "instrument": "JTPA training offer", "p": 0.0008309837419456675, "se": 314.32989833012556, "t": 3.343171883713256 } ] }Hashes SHA-256 e metadados de reprodução
- Digests dos dados
abadie_instrumental_variables7d1e5077d40b12f4726ea5b1690837de3f5067be68b661660c27c9d21475aa9d- sha256 do resultado
86ddecb5517fd6ae3c0cea62ca90a5b2ab17c7e8f91ecfc3551a3e044962ddae
- 3Turno do modelo
call_e4c2c1edreferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.iv_2sls): coef.JTPA training participation = 1679.", "caveats": [], "figure_refs": [ "call_952ea94c:coef.JTPA training participation" ] }
- 4Guardaresposta aceita
- Números encontrados
- 1679
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa (infer.iv_2sls): coef.JTPA training participation = 1679.
Figuras citadas:call_952ea94c:coef.JTPA training participation· Parada:answeredFigura da resposta:call_952ea94c:coef.JTPA training participation= 1.679,261679.2598927825413(se 501,612501.61212543563096) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta próximafalhouobrigatória
1679.259893 vs 1779.922
Épocas × verificações
| # | 0 | 1 |
|---|---|---|
| Época 1 | passou | falhou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1falhoupontuada(exibindo)
Downloads desta tarefa
2231fe006b3791aac34df7deee8cb41c2b37aa51b56b3fed394e823ad4754fb6O 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.
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|---|---|---|
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| native/causcibench_real/causcibench_real.q104.e1.a1.json | 2,0 KB | 252469529bd59e7be30d337b74ca6997f7a77de7407864f43be603bae2be580c |
| sources/causcibench_real.gold.q104.json | 1,2 KB | a7116f0b114b9d67b59f83a343ad6e25a4d749e7106495ed00b6c8897042d09d |
| specs/causcibench_real.q104.json | 6,9 KB | 08f534e6e13d008751e5e251d1b7934584314b03de35e66aebe823dda43c69fc |
| traces/causcibench_real.q104.e1.a1.jsonl | 17,6 KB | 810844b26f7276ff4a8ea990f2e646588c2d7e65cf6bd51afb10b2fdae4f300e |
| trajectories/causcibench_real.q104.e1.a1.jsonl | 14,3 KB | c37552d635cdb61591a49e40051fbf7c42f051f523518d690da2e3bf2a24135d |