Tarefa qrdata_socsci.395
qrdata_socsciagentT2publicépoca 1, tentativa 1Execução: 20261015T170025Z-suite-qrdata_socsci-baseline-2a40bfVeredito
no answer figure: the answer cites no effect of an estimator callPergunta feita ao analista
We standardize vote shares across elections by computing their z-scores so that we can measure Obama’s electoral performance in each state relative to his average performance of that year. That is, we subtract the mean from Obama’s vote share in each election and then divide it by the standard deviation. What is the proportion of states where Obama received a greater share of standardized votes in 2012 than he did in 2008, in the top quartile of Obama’s 2008 (standardized) vote share? Please round to the nearest thousandth.
Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.
Valores esperados e de onde vêm
qrdata.gold.395
- Fonte
- QRData benchmark/QRData.json at de450af45ff7101b328bb064c6b475f73414a7ed (Xiao Liu, Zirui Wu, Xueqing Wu, Pan Lu, Kai-Wei Chang, Yansong Feng. Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data. Findings of the Association for Computational Linguistics: ACL 2024, pages 9215-9235.)
- Tipo
- benchmark_gold
- Localização
- QRData.json item 395 (0-based), field 'answer'
- Trecho
item 395 answer 0.461
- Valor como publicado
0.461- Valor
- 0,461
0.461 - Conferido por
- arquivo do benchmark
- sha256 da cópia lida
e076d960f19434adf728aab70480ce34808c06066fcea48eaa38b145d1a111a1(identifica a cópia lida, não um arquivo canônico)- Endereço
https://raw.githubusercontent.com/xxxiaol/QRData/de450af45ff7101b328bb064c6b475f73414a7ed/benchmark/QRData.json- Licença
- CC BY-NC 4.0
- #1 figura da resposta próxima:
[0.44717,0.47483000000000003]· interval · [0.44717, 0.47483000000000003] ()
qrdata.eval_py
- Fonte
- QRData benchmark/eval.py at de450af45ff7101b328bb064c6b475f73414a7ed (Xiao Liu, Zirui Wu, Xueqing Wu, Pan Lu, Kai-Wei Chang, Yansong Feng. Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data. Findings of the Association for Computational Linguistics: ACL 2024, pages 9215-9235.)
- Tipo
- software
- Localização
- benchmark/eval.py: extract_first_number, calc_acc
- Valor
- —
- Conferido por
- arquivo do benchmark · Vendored byte for byte as suites/data/qrdata_socsci/vendor/benchmark_eval.py.txt; a parity test runs its functions against MAGI's port and the answer_figure_close check.
- Implementação
- independente da ferramenta
- sha256 da cópia lida
d6e5c1f7535ac9413951996c15544beb6f184244acb2da56e1fcd0942837e33d(identifica a cópia lida, não um arquivo canônico)- Endereço
https://raw.githubusercontent.com/xxxiaol/QRData/de450af45ff7101b328bb064c6b475f73414a7ed/benchmark/eval.py- Licença
- CC BY-NC 4.0
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number backed | obrigatória | passou | — | [] | — | — | — |
| 1 | figura da resposta próxima no answer figure: the answer cites no effect of an estimator call | obrigatória | falhou | [0.44717,0.47483000000000003] | — | interval · [0.44717, 0.47483000000000003] () | qrdata.gold.395 | — |
Caminho de referência e caminho do agente
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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
We standardize vote shares across elections by computing their z-scores so that we can measure Obama’s electoral performance in each state relative to his average performance of that year. That is, we subtract the mean from Obama’s vote share in each election and then divide it by the standard deviation. What is the proportion of states where Obama received a greater share of standardized votes in 2012 than he did in 2008, in the top quartile of Obama’s 2008 (standardized) vote share? Please round to the nearest thousandth.
pres08(agent)Regression towards the mean represents an empirical phenomenon where an observation with a value of the predictor further away from the distribution’s mean tends to have a value of an outcome variable closer to that mean. This tendency can be explained by chance alone. We will examine whether or not the US presidential election data exhibit the regression towards the mean phenomenon. To do this, we use Obama’s vote share in the 2008 election to predict his vote share in his 2012 reelection. The CSV data file pres08.csv contains the election results by state of the 2008 US presidential election. Variable Description state: abbreviated name of the state state.name: unabbreviated name of the state Obama: Obama’s vote share (percentage) McCain: McCain’s vote share (percentage) EV: number of Electoral College votes for the state In addition, we have the CSV file pres12.csv, which contains the election results by state of the 2012 US presidential election. Variable Description state: abbreviated name of the state Obama: Obama’s vote share (percentage) Romney: Romney’s vote share (percentage) EV: number of Electoral College votes for the state
file3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970· frame —pres12(agent)Data file pres12.csv of this question; the question's data description is the description of dataset 'pres08'.
file3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970· frame — - 1Turno do modelo
call_3def4436rules-1Fim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.", "caveats": [], "figure_refs": [] }
- 2Guardaresposta aceita
- Números encontrados
- —
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 3Resposta
Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.
Figuras citadas:—· Parada:answered - 4Pontuação#0resposta com lastropassouobrigatória
every number backed - 5Pontuação#1figura da resposta próximafalhouobrigatória
no answer figure: the answer cites no effect of an estimator call
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
2c6f11d20fce2972fa27819c75e6283a3b99637657d18182166d88fff1606e61O 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/3f79b2fa2bf5f8f6468425986a7e8f23f42a6bc87680fa073287313d49aac8db.json | 1,8 KB | 3f79b2fa2bf5f8f6468425986a7e8f23f42a6bc87680fa073287313d49aac8db |
| attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json | 2,4 KB | 433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420 |
| attachments/4c79c216fae647f816ee4847bbb0bb8cbea1c033c90b52b4850b8ebc2642dc3c.json | 570 B | 4c79c216fae647f816ee4847bbb0bb8cbea1c033c90b52b4850b8ebc2642dc3c |
| attachments/52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b.json | 64,0 KB | 52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b |
| native/qrdata_socsci/qrdata_socsci.395.e1.a1.json | 311 B | 0cdefd8def43180981f9952312acc7a6e8be0ad250275046d95f961fd7bffb1b |
| sources/qrdata.eval_py.json | 1,3 KB | d610b61f390d29ce767e08ce850eab5cb0dc4d13c1edb62d8cf3b0e49a3a291a |
| sources/qrdata.gold.395.json | 1,1 KB | 51e14124212c048b82fb8bd06719f72ffa9009b99351d62df5480d5f86c5dfe2 |
| specs/qrdata_socsci.395.json | 5,2 KB | 89737815867b0dcf4b3be143f2e4f206dda37a17233233614bb9a134d02ce269 |
| traces/qrdata_socsci.395.e1.a1.jsonl | 7,7 KB | c5857155bd0209790d1d3b73a2b0abcb2ad3cd52a39149a9f05f907fd2d931ee |
| trajectories/qrdata_socsci.395.e1.a1.jsonl | 5,3 KB | 297ac10240c1481716364d9e41b8b39d0f9476b4711a0ff11e2995e955d07814 |