{"attempt":1,"datasets":{"cheng_does_strengthening":{"description_shown":"This dataset examines the impact of castle-doctrine statutes on violent crime rates in the United States. It combines state-level crime data from the FBI Uniform Crime Reports (UCR) Summary Files with information on the timing of castle-doctrine law implementation across states. The laws were adopted at different times, with 21 states enacting them between 2000 and 2010.\n\nDataset Variables:\nyear: Calendar year\npost: Indicator for post-treatment period\nsid: State ID\nrobbery_gun_r: Region-quarter fixed effect (robbery with gun)\njhcitizen_c: Justifiable homicides by private citizens\njhpolice_c: Justifiable homicides by police officers\nhomicide: Homicide rate per 100,000 state population\nrobbery: Robbery rate per 100,000 state population\nassault: Aggravated assault rate per 100,000 state population\nburglary: Burglary rate per 100,000 state population\nlarceny: Larceny rate per 100,000 state population\nmotor: Motor vehicle theft rate per 100,000 state population\nmurder: Murder rate per 100,000 state population\nl_homicide: Log of homicide rate\nl_robbery: Log of robbery rate\nl_assault: Log of aggravated assault rate\nl_burglary: Log of burglary rate\nl_larceny: Log of larceny rate\nl_motor: Log of motor vehicle theft rate\nl_murder: Log of murder rate\nunemployrt: State unemployment rate\nblackm_15_24: Percent of Black males aged 15 to 24\nwhitem_15_24: Percent of White males aged 15 to 24\nblackm_25_44: Percent of Black males aged 25 to 44\nwhitem_25_44: Percent of White males aged 25 to 44\npoverty: State poverty rate\nl_police: Logged police presence\nl_income: Logged income\nl_prisoner: Logged number of prisoners\nl_lagprisoner: Lagged log prisoners\nl_exp_subsidy: Logged subsidy spending\nl_exp_pubwelfare: Logged public welfare spending\nlead1, lead2, lead3, lead4, lead5, lead6, lead7, lead8, lead9, lag0, lag1, lag2, lag3, lag4, lag5: Indicators of how many time periods until/since treatment\npopwt: Population weight\nr20001, r20002, r20003, r20004, r20011, r20012, r20013, r20014, r20021, r20022, r20023, r20024, r20031, r20032, r20033: Region-quarter fixed effects\ntrend_1, trend_10, trend_11, trend_12, trend_13, trend_14, trend_15, trend_16, trend_17, trend_18, trend_19: linear time trends","file_sha256":"b84b3549a35f5322b7d6adaa8030c435fdcd26bbb63eea02e24883c1dc6f7fed","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"What is the effect of castle doctrine laws on (log) motor vehicle theft rates?","question_sha256":"c48f1bf49e2acd231145303ef9233b261e3db0e0fe52b7c6eba8e0a69aa3ed1e","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":0,"skills":[],"task_id":"causcibench_real.q016","task_sha256":"e08e997a3f6dd6567270b71c5a262dc64d5eaa533f7c0b85f8d15b2275d3569e","timestamp":"2026-10-15T17:11:00.078376Z"}
{"attempt":1,"attempts":[],"call_id":"call_c0a33066","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"reference","model_requested":"reference","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["63def280845a474a1756469fbca8530bf58058926c358f413c7312059c0438db"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"d1caebc365e96699436c5f20d2feaa1637951a90c37466ad7550a6f0e930e3cf","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"causcibench_metadata_rule/1: did","thoughts":null,"tool_calls":[{"args":{"controls":[],"dataset":"cheng_does_strengthening","fe":["sid","year"],"x":["cdl"],"y":"l_motor"},"llm_name":"infer__ols","tool_id":"infer.ols","vendor_id":"script_1"}]},"response_id":null,"run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":1,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.078376Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"arguments":{"cluster":null,"controls":[],"dataset":"cheng_does_strengthening","fe":["sid","year"],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["cdl"],"y":"l_motor"},"attempt":1,"cached":false,"call_id":"call_334902aa","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"cheng_does_strengthening":"1138e3007dbd4dbbf767590fa8e58b9a3e35a279edeb3fab5066342fdf58bb77"},"decided_by":"model","duration_ms":14.14074981585145,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"3ea70793b27027a8769259748edf6109aa9029c523da9db6f09a066b1ad8c30d","llm_name":"infer__ols","output_digest":"152c65334abd09bbd4260616333ae81a0bd9f54dfd15b8d28b37d4553263ebd4","rationale":"causcibench_metadata_rule/1: did","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_334902aa","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":550},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":61},{"flag":false,"name":"r2","note":"","value":0.9581547077665671},{"flag":false,"name":"df_resid","note":"","value":489},{"flag":false,"name":"se_type","note":"heteroskedasticity-robust standard errors (HC1)","value":"HC1"},{"flag":false,"name":"n_clusters","note":"errors not clustered","value":null},{"flag":false,"name":"fixed_effects","note":"absorbed as dummies; their coefficients are not tabulated","value":"sid (50 levels), year (11 levels)"}],"figures":[{"ci_high":0.11800679897056152,"ci_level":0.95,"ci_low":0.03530090009902723,"derivation":{"note_pt":"","steps":[{"formula":"","result":0.07665384953479437,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":550.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":61.0}],"text_pt":"Coeficiente de cdl na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de l_motor, efeitos fixos de sid, year.","unit":""},{"formula":"ep = \u221aV_jj","result":0.021046610079155148,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.00044295979582399507}],"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":0.07665384953479437},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9648270804771393},{"note":"","symbol":"ep","unit":"","value":0.021046610079155148}],"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 489 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.cdl","label":"Coefficient on cdl in the regression of l_motor","se":0.021046610079155148,"unit":"","value":0.07665384953479437}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":5.8545237660388745,"ci_low":5.715802260791087,"coef":5.785163013414981,"p":0.0,"se":0.035301199435346514,"t":163.88006940133573,"term":"Intercept"},{"ci_high":0.11800679897056152,"ci_low":0.03530090009902723,"coef":0.07665384953479437,"p":0.0002992924836259781,"se":0.021046610079155148,"t":3.642099570738634,"term":"cdl"}]},"tool":"infer.ols","version":"0.1.0","warnings":[]},"result_for_model_ref":"f151ba22346e70a9142b09c1857c8f0f964914e84feb113999f901fc6025638b","result_sha256":"bec724f0f2522711a2877b26609c76a98b950b15f9b40d6a1ee5e1accfa263c1","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":2,"synthetic":false,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.081116Z","tool_id":"infer.ols","turn_id":"call_c0a33066"}
{"attempt":1,"attempts":[],"call_id":"call_b782855a","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"reference","model_requested":"reference","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["63def280845a474a1756469fbca8530bf58058926c358f413c7312059c0438db","117c047b2df6dbd3a4d5cde455cb13fb6a40eb9701f80e5192b9946d38cf0574","a9435f182824fe3629046f18615f14619f1de2510fc506d11ef3ffc0d6dd13a1"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"d1caebc365e96699436c5f20d2feaa1637951a90c37466ad7550a6f0e930e3cf","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"","thoughts":null,"tool_calls":[{"args":{"answer":"Estimativa (infer.ols): coef.cdl = 0,07665.","caveats":[],"figure_refs":["call_334902aa:coef.cdl"]},"llm_name":"submit_answer","tool_id":null,"vendor_id":"script_2"}]},"response_id":null,"run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":3,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.095438Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"attempt":1,"call_id":"call_7579b8b2","epoch":1,"event":"guard","numbers_found":["0,07665"],"retries_left":1,"run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":4,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.097111Z","turn_id":"call_b782855a","unbacked":[],"uncited":[],"verdict":"accepted"}
{"answer":"Estimativa (infer.ols): coef.cdl = 0,07665.","answer_figure":{"call_id":"call_334902aa","ci_high":0.11800679897056152,"ci_low":0.03530090009902723,"formatted":0.07665384953479437,"key":"coef.cdl","ref":"call_334902aa:coef.cdl","se":0.021046610079155148,"tool_id":"infer.ols","unit":"","value":0.07665384953479437},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_334902aa:coef.cdl"],"run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":5,"stopped":"answered","task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.097269Z"}
{"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":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":6,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.097269Z"}
{"attempt":1,"check":{"check_index":1,"detail":"0.07665384953 vs 0.077","expected":0.077,"failure_class":null,"kind":"answer_figure_close","observed":0.07665384953479437,"passed":true,"required":true,"source_id":"causcibench_real.gold.q016","tolerance":{"abs_tol":null,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":0.05,"rule":null},"trace_call_id":"call_334902aa","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":7,"task_id":"causcibench_real.q016","timestamp":"2026-10-15T17:11:00.097269Z"}