{"attempt":1,"datasets":{"manacorda_gov_transfers":{"description_shown":"The data focuses on the Uruguayan Plan de Atencion Nacional a la Emergencia Social (PANES), described as a large, temporary social relief program. PANES ran from April 2005 to December 2007. PANES included several components. The main part was a monthly cash transfer. Eligibility for the PANES program was determined using a predicted income score. This score was based on household socioeconomic characteristics collected during a baseline survey. Households were eligible only if their predicted income score fell below a predetermined threshold.\n\nVariables:\nincome_centered: Income measure, centered around program cutoff (negative value = eligible)\neducation: Household average years of education among those 16+\nage: Household average age\nparticipation: Participation in transfers (1 = participated, 0 = did not participate)\nsupport: Measure of support for the government","file_sha256":"a25fd9493a2f57e990d7769905fe56374bc6ddad9534e88c8d01085812fb0334","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"Did receiving financial assistance from Uruguay's poverty alleviation program cause recipients to view the government more favorably?","question_sha256":"9aff8777c48175f62e9d5673a971b02e9071e4ce8a0c10ae78d90361ccb9d6c1","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":0,"skills":[],"task_id":"causcibench_real.q019","task_sha256":"34d5726d427e00487a62b62806654e20a0d215aff1859a98540e5c37c7eeb702","timestamp":"2026-10-15T17:11:43.112923Z"}
{"attempt":1,"attempts":[],"call_id":"call_ac1704d9","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"naive-ols","model_requested":"naive-ols","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["f36270888cc600966498a6ebba4537a7b302ebdff351ea7deb9bbcc2823d8183"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"ff47843a700e0e15ddbf4fcf7ad8b67853efe5b4adea0c00853df5e0f8409484","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","thoughts":null,"tool_calls":[{"args":{"dataset":"manacorda_gov_transfers","x":["participation"],"y":"support"},"llm_name":"infer__ols","tool_id":"infer.ols","vendor_id":"script_1"}]},"response_id":null,"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":1,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.112923Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"arguments":{"cluster":null,"controls":[],"dataset":"manacorda_gov_transfers","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["participation"],"y":"support"},"attempt":1,"cached":false,"call_id":"call_6f766c74","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"manacorda_gov_transfers":"545db619c654ede637c18214cd75e71504b965d091a1f70f0af6dee6e4ec7827"},"decided_by":"model","duration_ms":17.980791861191392,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"fbd678a9545cd5a480fea43c012d13178ec612793ede4fea05e5f847a920c98c","llm_name":"infer__ols","output_digest":"b08d5a719593372851f9642df66356c3c44d55b9e0797d13e863966a2f17f4c6","rationale":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","replay_class":"replayed","result":{"assumptions":["the conditional mean of the outcome is linear in the regressors","errors are independent across observations; their variance may differ"],"call_id":"call_6f766c74","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":1948},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":0.033715944281967},{"flag":false,"name":"df_resid","note":"","value":1946},{"flag":false,"name":"se_type","note":"heteroskedasticity-robust standard errors (HC1)","value":"HC1"},{"flag":false,"name":"n_clusters","note":"errors not clustered","value":null}],"figures":[{"ci_high":0.14730553196827195,"ci_level":0.95,"ci_low":0.08925537423501856,"derivation":{"note_pt":"","steps":[{"formula":"","result":0.11828045310164526,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":1948.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de participation na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de support.","unit":""},{"formula":"ep = \u221aV_jj","result":0.014799775094998522,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.00021903334286253853}],"text_pt":"Erro-padr\u00e3o robusto \u00e0 heterocedasticidade (HC1): a raiz da vari\u00e2ncia estimada do coeficiente.","unit":""},{"formula":"IC = \u03b2 \u00b1 c \u00b7 ep","result":null,"terms":[{"note":"","symbol":"\u03b2","unit":"","value":0.11828045310164526},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9611837801802485},{"note":"","symbol":"ep","unit":"","value":0.014799775094998522}],"text_pt":"Intervalo de 95% de confian\u00e7a: a estimativa mais ou menos o valor cr\u00edtico da distribui\u00e7\u00e3o t de Student com 1946 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.participation","label":"Coefficient on participation in the regression of support","se":0.014799775094998522,"unit":"","value":0.11828045310164526}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":0.751540033120025,"ci_low":0.7040019888044573,"coef":0.7277710109622412,"p":0.0,"se":0.012119732172983459,"t":60.04844006244151,"term":"Intercept"},{"ci_high":0.14730553196827195,"ci_low":0.08925537423501856,"coef":0.11828045310164526,"p":2.252468500729433e-15,"se":0.014799775094998522,"t":7.992043956236692,"term":"participation"}]},"tool":"infer.ols","version":"0.1.0","warnings":[]},"result_for_model_ref":"792b06b0609d6e8b32cb4ad1c715337d5cb2dc46e4ce7991f33ec99b7f05069d","result_sha256":"7f6c22d644ccf6efadffa6de7f9d68c441531f58a815490cad56521657bade66","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":2,"synthetic":false,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.115910Z","tool_id":"infer.ols","turn_id":"call_ac1704d9"}
{"attempt":1,"attempts":[],"call_id":"call_04c91f74","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"naive-ols","model_requested":"naive-ols","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["f36270888cc600966498a6ebba4537a7b302ebdff351ea7deb9bbcc2823d8183","a8f841059fabe10b678b3455bc87fcbcb703d97adfe66321f1dff28cd1932d5e","b63bc98f15745831430fd86180bbc806cb17b37201bc184f04749b93270e95fd"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"ff47843a700e0e15ddbf4fcf7ad8b67853efe5b4adea0c00853df5e0f8409484","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"","thoughts":null,"tool_calls":[{"args":{"answer":"Estimativa ing\u00eanua (infer.ols): coef.participation = 0,1183.","caveats":[],"figure_refs":["call_6f766c74:coef.participation"]},"llm_name":"submit_answer","tool_id":null,"vendor_id":"script_2"}]},"response_id":null,"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":3,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.134038Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"attempt":1,"call_id":"call_83a52729","epoch":1,"event":"guard","numbers_found":["0,1183"],"retries_left":1,"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":4,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.136241Z","turn_id":"call_04c91f74","unbacked":[],"uncited":[],"verdict":"accepted"}
{"answer":"Estimativa ing\u00eanua (infer.ols): coef.participation = 0,1183.","answer_figure":{"call_id":"call_6f766c74","ci_high":0.14730553196827195,"ci_low":0.08925537423501856,"formatted":0.11828045310164526,"key":"coef.participation","ref":"call_6f766c74:coef.participation","se":0.014799775094998522,"tool_id":"infer.ols","unit":"","value":0.11828045310164526},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_6f766c74:coef.participation"],"run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":5,"stopped":"answered","task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.136406Z"}
{"attempt":1,"check":{"check_index":0,"detail":"every number backed","expected":null,"failure_class":null,"kind":"answer_backed","observed":[],"passed":true,"required":true,"source_id":null,"tolerance":null,"trace_call_id":null,"weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":6,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.136406Z"}
{"attempt":1,"check":{"check_index":1,"detail":"0.1182804531 vs 0.093","expected":0.093,"failure_class":"out_of_tolerance","kind":"answer_figure_close","observed":0.11828045310164526,"passed":false,"required":true,"source_id":"causcibench_real.gold.q019","tolerance":{"abs_tol":null,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":0.05,"rule":null},"trace_call_id":"call_6f766c74","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":7,"task_id":"causcibench_real.q019","timestamp":"2026-10-15T17:11:43.136406Z"}
