Tarefa causcibench_real.q089
causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171142Z-suite-causcibench_real-naive-d6494dVeredito
0.2815248252 vs 0.222Família do método (das chamadas de ferramentas): ols (regression)
Pergunta feita ao analista
How does the local proportion of GP‑to‑specialist cancer referrals that breach the two‑week wait standard affect individuals' reported trust in the NHS on a 1–7 scale?
Estimativa ingênua (infer.ols): coef.cancerDelay = 0,2815.
Valores esperados e de onde vêm
causcibench_real.gold.q089
- Fonte
- CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 89
- Tipo
- benchmark_gold
- Localização
- real_input.json, record id 89: fields effect and std_error
- Trecho
id 89 effect 0.222 std_error 0.197
- Valor como publicado
0.222- Erro-padrão como publicado
0.197- Valor
- 0,222
0.222(se 0,1970.197) - 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: 0,222
0.222· relativa 0.05
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number backed | obrigatória | passou | — | [] | — | — | — |
| 1 | figura da resposta próxima 0.2815248252 vs 0.222 | obrigatória | falhou | 0,2220.222 | 0,2815250.28152482522268996 | relativa 0.05 | causcibench_real.gold.q089 | call_2fc9014a |
Caminho de referência e caminho do agente
A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.
Nenhum caminho de referência registrado para esta tarefa.
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
How does the local proportion of GP‑to‑specialist cancer referrals that breach the two‑week wait standard affect individuals' reported trust in the NHS on a 1–7 scale?
dorussen_the_influence(agent)This dataset contains individual-level survey responses from adults in England merged with local NHS performance measures on emergency and cancer referral waits covering July 2022 to July 2023. Each row corresponds to a respondent observation with institutional trust ratings, demographics, constituency-level context, and area-level waiting-time indicators linked via postcode outcodes to NHS Integrated Care Boards (ICBs) and ICB sub-units. Variable descriptions: id: Anonymous respondent identifier that uniquely indexes each survey record within the merged file trustGov: Self-reported trust in ""the Government in Westminster"" on a 1-7 scale where 1 = Not at all and 7 = Completely trustPM: Self-reported trust in the Prime Minister on the same 1-7 scale trustParl: Self-reported trust in the UK Parliament on the 1-7 scale trustMP: Self-reported trust in the respondent's local Member of Parliament on the 1-7 scale trustNHS: Self-reported trust in the National Health Service on the 1-7 scale trustPolice: Self-reported trust in the police on the 1-7 scale trustCourts: Self-reported trust in the courts on the 1-7 scale trustTradNews: Self-reported trust in news from traditional media on the 1-7 scale trustSocNews: Self-reported trust in news shared on social media on the 1-7 scale income: Personal annual income category with 14 brackets (under 5,000; 5,000-9,999; ...; 100,000+) emergencyDelay: Proportion of patients waiting more than 4 hours from decision to admit to admission across all A&E types in the respondent's ICB cancerDelay: Proportion of GP-to-specialist cancer referrals breaching the two-week wait standard in the respondent's ICB sub-unit over July 2022-June 2023 ethnicity: Indicator for membership in an ethnic minority group, derived from survey responses/profile variables london: Indicator for residence in the London region as defined in the nine-region classification used in the survey conVote19: Indicator for whether the respondent reported voting Conservative in the 2019 UK General Election women: Indicator for respondent's sex coded as female based on survey demographics higherEd: Indicator for completion of higher education as reported in the survey region: Categorical variable for the nine regions of England used to locate respondents conShare: Conservative Party vote share (%) in the respondent's parliamentary constituency at the 2019 General Election unemploymentRate: Constituency-level unemployment rate (%) matched to each respondent's parliamentary constituency age: Respondent age in years (real-valued), spanning 18-98 across waves W8: Respondent-level survey weight provided by the survey vendor for national representativeness across pooled monthly waves
file08184bd4fe64bbecf97d1896551a9f9adcb9b55fc6999acbcf130e7653e69ec9· frame — - 1Turno do modelo
call_416922bfnaive-olsFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelLinha de base ingênua: regressão do resultado no tratamento, sem controles.
Chamadas pedidasinfer.ols{ "dataset": "dorussen_the_influence", "x": [ "cancerDelay" ], "y": "trustNHS" }
- 2Ferramenta
infer.olsv0.1.0call_2fc9014adecidido pelo modeloreexecutávelMotivo: Linha de base ingênua: regressão do resultado no tratamento, sem controles.
Argumentos
{ "cluster": null, "controls": [], "dataset": "dorussen_the_influence", "fe": [], "intercept": true, "level": 0.95, "se": "HC1", "subset": null, "weights": null, "x": [ "cancerDelay" ], "y": "trustNHS" }Figuras call_2fc9014a Chave Valor Valor bruto Erro-padrão IC coef.cancerDelay Coefficient on cancerDelay in the regression of trustNHS0,281525 0.281524825222689960,146884 0.146884354360049-0,00641505 – 0,569465 Diagnósticosn_obs= 6.7266726k= 22r2= 0,0005301620.0005301615286864569df_resid= 6.7246724se_type="HC1"n_clusters= —
Tabelas (1)
{ "coefficients": [ { "ci_high": 4.979688662072992, "ci_low": 4.838968393518473, "coef": 4.909328527795733, "p": 0, "se": 0.0358922253567103, "t": 136.7797198141101, "term": "Intercept" }, { "ci_high": 0.569464700593764, "ci_low": -0.0064150501483840605, "coef": 0.28152482522268996, "p": 0.05532568072379405, "se": 0.146884354360049, "t": 1.9166426979186948, "term": "cancerDelay" } ] }- Digests dos dados
dorussen_the_influence378acc9f5ca587819e3eb096a0bb4b7fa1011f6549b89f0efef3a2e3dd31aa69- sha256 do resultado
7defc786f618f450481d001ea41a597acc7b41fd37f9cc6ef2931a6c6d46619e
- 3Turno do modelo
call_0e31cee9naive-olsFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa ingênua (infer.ols): coef.cancerDelay = 0,2815.", "caveats": [], "figure_refs": [ "call_2fc9014a:coef.cancerDelay" ] }
- 4Guardaresposta aceita
- Números encontrados
- 0,2815
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa ingênua (infer.ols): coef.cancerDelay = 0,2815.
Figuras citadas:call_2fc9014a:coef.cancerDelay· Parada:answeredFigura da resposta:call_2fc9014a:coef.cancerDelay= 0,2815250.28152482522268996(se 0,1468840.146884354360049) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta próximafalhouobrigatória
0.2815248252 vs 0.222
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
fb0e049dfa5e66bd7a44e2d3cbe4e238c34c758098bc5e151132855fe256cebbO 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.
| Arquivo | Tamanho | sha256 |
|---|---|---|
| attachments/23b3db2ff4e7e021e17662af179951157fca08d36b30dea535fd1447b0ff3a53.json | 247 B | 23b3db2ff4e7e021e17662af179951157fca08d36b30dea535fd1447b0ff3a53 |
| attachments/33c940486d024f959093ae32b689c9fa822d4908807bfabe8789b4e78be698cc.json | 212 B | 33c940486d024f959093ae32b689c9fa822d4908807bfabe8789b4e78be698cc |
| attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json | 2,4 KB | 433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420 |
| attachments/50e6b8dcbe90497699d67798ebf9297dc84488939e39a6a40333d123bcc8122e.json | 3,6 KB | 50e6b8dcbe90497699d67798ebf9297dc84488939e39a6a40333d123bcc8122e |
| attachments/52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b.json | 64,0 KB | 52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b |
| attachments/af6cec1f724c8d70d665a6ad0ae040e5ce7e42540bd556cd62a65c99897dc315.json | 882 B | af6cec1f724c8d70d665a6ad0ae040e5ce7e42540bd556cd62a65c99897dc315 |
| attachments/f7f40caf6320b5680411816db502ec7a79222ac4ac3139e067eec5dd79e773c1.json | 988 B | f7f40caf6320b5680411816db502ec7a79222ac4ac3139e067eec5dd79e773c1 |
| native/causcibench_real/causcibench_real.q089.e1.a1.json | 1,8 KB | d354a7f2fc10a6d6daa79e393f860c9ff605f5d07de429d91b9988066b9d6419 |
| sources/causcibench_real.gold.q089.json | 1,2 KB | b8ce7bc2f4e373799bf9930f3a233b4af05bfd1bbda16945d89ab1a790f54086 |
| specs/causcibench_real.q089.json | 6,9 KB | 19aa56b12b1efd7c62488be0efe1926d3d189801f59b8823c0e592127448cd68 |
| traces/causcibench_real.q089.e1.a1.jsonl | 14,5 KB | ed79733025886c0877498d01083f600ee5a8e449cbb3df6fd3f152eebebd5fd6 |
| trajectories/causcibench_real.q089.e1.a1.jsonl | 11,3 KB | 9eba02d7a190af6f1d22854e14a17cd011025d084147ab9e61bc465452ebaec1 |