Tarefa causcibench_real.q098
causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01dVeredito
0.09871020362 vs 0.086Família do método (das chamadas de ferramentas): rd (regression discontinuity)
Pergunta feita ao analista
In the UK, in very close elections, does just barely winning make it more likely that the party's candidate will stand again as the incumbent in the next election?
Estimativa (infer.rdd): effect = 0,09871.
Valores esperados e de onde vêm
causcibench_real.gold.q098
- Fonte
- CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 98
- Tipo
- benchmark_gold
- Localização
- real_input.json, record id 98: fields effect and std_error
- Trecho
id 98 effect 0.086 std_error 0.031
- Valor como publicado
0.086- Erro-padrão como publicado
0.031- Valor
- 0,086
0.086(se 0,0310.031) - 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: 0,086
0.086· 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 0.09871020362 vs 0.086 | obrigatória | falhou | 0,0860.086 | 0,09871020.09871020361757638 | relativa 0.05 | causcibench_real.gold.q098 | call_878d39bc |
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 · hand_inferred
| Argumento | Referência | Agente | |
|---|---|---|---|
| bandwidth | — | — | não fixado pela referência |
| cluster | — | — | não fixado pela referência |
| cutoff | 00 | 00 | igual |
| dataset | "song_estimating_incumbency" | "song_estimating_incumbency" | igual |
| kernel | — | "triangular" | não fixado pela referência |
| level | — | 0,950.95 | não fixado pela referência |
| polynomial | — | 11 | não fixado pela referência |
| running | "l_vmargin" | "l_vmargin" | igual |
| subset | — | — | não fixado pela referência |
| y | "win" | "win" | igual |
Pendências do caminho de referência: needs_spec:cutoff, needs_spec:side, needs_spec:bandwidth, needs_spec:sample
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
In the UK, in very close elections, does just barely winning make it more likely that the party's candidate will stand again as the incumbent in the next election?
song_estimating_incumbency(agent)The dataset is a panel of electoral constituencies across multiple countries and years, designed to study incumbency effects. Each row corresponds to a party's performance in a given constituency at a given election. Dataset Variables: year: The year of the election country: The country where the election took place (e.g., Canada, Japan, UK, USA, Romania, etc.) office: Name of the office being contested (e.g., House of Commons, Mayor) cst_n: Constituency identifier (e.g., ""abbotsford"", ""abitibi"") l_vmargin: Lagged vote margin: the party's vote margin in the previous election (Values more than 0 indicate the party won (positive) and values less than 0 indicate the party lost (negative)) vmargin: Current vote margin: the party's vote margin in the current election vs: Vote share of the party in the current election (between 0 and 1) win: Outcome of the current election: 1 means the party won the seat, 0 means the party lost l_win: Lagged win indicator: 1 means the party won the previous election in this constituency, 0 means the party lost inc: Incumbency indicator for the party's candidate in the current election: 1 means candidate is the incumbent, 0 means not incumbent, -1 appears to mark cases where incumbency is undefined or missing office_num: Encoded office type, combining country and office (e.g., Canada, House) rd_s: Indicator variable that equals 1 if the observation is part of a subset of elections defined by narrow vote margins, and 0 otherwise
filef9455065815897f357981f2f97871fe8b7137acf6ef1b2772241d4bf05de9b10· frame — - 1Turno do modelo
call_9b0f08fcreferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelcauscibench_metadata_rule/1: rdd
Chamadas pedidasinfer.rdd{ "cutoff": 0, "dataset": "song_estimating_incumbency", "running": "l_vmargin", "y": "win" }
- 2Ferramenta
infer.rddv0.1.0call_878d39bcdecidido pelo modeloreexecutávelMotivo: causcibench_metadata_rule/1: rdd
Argumentos
{ "bandwidth": null, "cluster": null, "cutoff": 0, "dataset": "song_estimating_incumbency", "kernel": "triangular", "level": 0.95, "polynomial": 1, "running": "l_vmargin", "subset": null, "y": "win" }Figuras call_878d39bc Chave Valor Valor bruto Erro-padrão IC effect Jump in win at the cutoff of l_vmargin0,0987102 0.098710203617576380,0163818 0.0163817526879525240,0666026 – 0,130818 Diagnósticosbandwidth= 0,1053170.1053167716797159bandwidth_method="IK"n_left= 8.0468046n_right= 8.4598459kernel="triangular"polynomial= 11bandwidth_sensitive=falsen_obs= 57.18757187se_type="HC1"
Tabelas (1)
{ "sensitivity": [ { "bandwidth": 0.05265838583985795, "ci_high": 0.13529238135744426, "ci_low": 0.04547169666360212, "estimate": 0.09038203901052319, "multiplier": 0.5, "n_left": 4266, "n_right": 4455, "se": 0.02291386102049228 }, { "bandwidth": 0.1053167716797159, "ci_high": 0.13081784888960554, "ci_low": 0.06660255834554721, "estimate": 0.09871020361757638, "multiplier": 1, "n_left": 8046, "n_right": 8459, "se": 0.016381752687952524 }, { "bandwidth": 0.2106335433594318, "ci_high": 0.14556329994591158, "ci_low": 0.09953818771028664, "estimate": 0.1225507438280991, "multiplier": 2, "n_left": 14278, "n_right": 14796, "se": 0.011741315809541695 } ] }- 966 rows were dropped because one of 'win', 'l_vmargin' was missing
- Digests dos dados
song_estimating_incumbencyb92d2fca9483051609676957c56c11b23d396f4044f39bece8e32f8049a0c08d- sha256 do resultado
29fbea3cb8f969f3664d909f32d99435720101452fda5c452e3a10881df53704
- 3Turno do modelo
call_8b9c7e1areferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.rdd): effect = 0,09871.", "caveats": [], "figure_refs": [ "call_878d39bc:effect" ] }
- 4Guardaresposta aceita
- Números encontrados
- 0,09871
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa (infer.rdd): effect = 0,09871.
Figuras citadas:call_878d39bc:effect· Parada:answeredFigura da resposta:call_878d39bc:effect= 0,09871020.09871020361757638(se 0,01638180.016381752687952524) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta próximafalhouobrigatória
0.09871020362 vs 0.086
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
0a3f63952e7e9fca5814e44e3b61d0b8b5f0b0a99bb9e9a93444e094a6a10c6cO 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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| native/causcibench_real/causcibench_real.q098.e1.a1.json | 1,7 KB | 5c66d73b9de1de8ab816d3a69bbddaa8aa376154db0ed39c2179db151bc77ef1 |
| sources/causcibench_real.gold.q098.json | 1,2 KB | d6408bad4fdb369101b9ccaa34c34a49ff0b4156a35ff008e0d22f5e0a8a37db |
| specs/causcibench_real.q098.json | 6,0 KB | 59bd365344197d583a3a24f2afc0247ad6397b9a1a5b3f72e08f0577a9f2e1d6 |
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| trajectories/causcibench_real.q098.e1.a1.jsonl | 10,8 KB | 0f2738b48c57effccbd3b3d6efdac627a19960528baafeff5392a55242bfec68 |