{"attempt":1,"datasets":{"carpenter_the_minimum_legal":{"description_shown":"This dataset aggregates near-census administrative records of emergency department visits and inpatient hospital admissions for U.S. young adults into age-in-months bins around the 21st birthday, with outcomes expressed as rates per 10,000 person-years by cause, gender, pregnancy exclusion, and contributing state tags where available. Age-running variables index months relative to 21, along with pre/post age polynomials and an indicator for the 21st-birthday month to accommodate birthday-month spikes documented in alcohol intoxication visits.\n\nVariables:\nmonths_21: Integer months relative to the 21st birthday (e.g., -24 to +24), indexing the running age variable used to organize age-specific rates\nage: Age reported in years corresponding to the same age-month cell, provided for convenience alongside months_21\nbmonth: Indicator equal to 1 for the month containing the 21st birthday (the \"\"birthday month\"\" control used to accommodate celebration spikes), 0 otherwise\npost: Indicator equal to 1 for observations at or above age 21 in months (post-threshold), 0 otherwise\nlinear, linear_post: Linear age terms for pre- and post-threshold segments, capturing smooth age trends on either side of age 21 within the specified bandwidth\nage_months: Age in months as a non-centered index (e.g., from 228 to 276), facilitating alternative specifications and diagnostics\nage_c, age_c_sq: Age in months centered at 21 (0 at 21) and its square for flexible smooth trends\nover: Synonym for post (equals 1 at and after 21), supplied for alternate coding conventions in estimation\nage_c_post, age_c_post_sq: Interactions of centered age and its square with the post indicator to allow different slopes/curvature after 21\ndummy21: Binary flag for the 21st-birthday month, identical in purpose to bmonth for absorbing discrete celebration effects in that month\nvisit_all_r: All non-pregnancy-screened ED visits per 10,000 person-years in the age-month cell\nalcohol_any_all_r: ED visits with primary alcohol intoxication coding per 10,000\ninjury_all_r: ED visits for any injury cause per 10,000\ninj_by_self_all_r / inj_by_oth_all_r / inj_accident_all_r: ED visits per 10,000 for self-inflicted injuries, injuries inflicted by others, and accidental injuries, respectively\nillness_all_r: ED visits per 10,000 for residual illness (non-alcohol, non-injury)\ninjury_or_alc_all_r: Composite of injury or alcohol intoxication ED visits per 10,000; visit_all_np_r, alcohol_any_all_np_r, injury_all_np_r, inj_by_self_all_np_r, inj_by_oth_all_np_r, inj_accident_all_np_r, illness_all_np_r, injury_or_alc_all_np_r: Same definitions as \"\"all_r\"\" but excluding pregnancy-related encounters, aligning with the study's analytic sample\nvisit_m_r, alcohol_any_m_r, injury_m_r, inj_by_self_m_r, inj_by_oth_m_r, inj_accident_m_r, illness_m_r, injury_or_alc_m_r: Male-only ED rates per 10,000 by cause\nvisit_f_r, alcohol_any_f_r, injury_f_r, inj_by_self_f_r, inj_by_oth_f_r, inj_accident_f_r, illness_f_r, injury_or_alc_f_r: Female-only ED rates per 10,000 by cause\nvisit_f_np_r, alcohol_any_f_np_r, injury_f_np_r, inj_by_self_f_np_r, inj_by_oth_f_np_r, inj_accident_f_np_r, illness_f_np_r, injury_or_alc_f_np_r: Female-only non-pregnancy ED rates per 10,000 by cause\nvisit_az_np_r, alcohol_any_az_np_r, injury_az_np_r, inj_by_self_az_np_r, inj_by_oth_az_np_r, inj_accident_az_np_r, illness_az_np_r, injury_or_alc_az_np_r: Arizona-specific ED rates per 10,000 (non-pregnancy), by cause\nvisit_ca_np_r, alcohol_any_ca_np_r, injury_ca_np_r, inj_by_self_ca_np_r, inj_by_oth_ca_np_r, inj_accident_ca_np_r, illness_ca_np_r, injury_or_alc_ca_np_r: State-tagged ED rates provided where available in replication files, analogous definitions as above\nvisit_ia_np_r, alcohol_any_ia_np_r, injury_ia_np_r, inj_by_self_ia_np_r, inj_by_oth_ia_np_r, inj_accident_ia_np_r, illness_ia_np_r, injury_or_alc_ia_np_r: State-tagged ED rates provided where available in replication files, analogous definitions as above\nvisit_nj_np_r, alcohol_any_nj_np_r, injury_nj_np_r, inj_by_self_nj_np_r, inj_by_oth_nj_np_r, inj_accident_nj_np_r, illness_nj_np_r, injury_or_alc_nj_np_r: New Jersey-specific ED rates per 10,000 (non-pregnancy), by cause\nvisit_wi_np_r, alcohol_any_wi_np_r, injury_wi_np_r, inj_by_self_wi_np_r, inj_by_oth_wi_np_r, inj_accident_wi_np_r, illness_wi_np_r, injury_or_alc_wi_np_r: Wisconsin-specific ED rates per 10,000 (non-pregnancy), by cause","file_sha256":"e49a7ad686067a4e4e119b7ab85a0dc1a8e562b1b5fc83d3f4e1d9b4b626d6e4","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"Does gaining legal access to alcohol at the U.S. minimum legal drinking age cause an increase in nonfatal morbidity?","question_sha256":"757d884e6fbb26947fc783919b67e9d692f846a9fece05cce56f547a5829327b","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":0,"skills":[],"task_id":"causcibench_real.q054","task_sha256":"0d823c3b2a514ffe2385ecd8b304d6a6a906bbe7f25bda6cfea82de454223d77","timestamp":"2026-10-15T17:11:00.764688Z"}
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{"arguments":{"cluster":null,"controls":["months_21","dummy21","age_c","age_c_sq","age_c_post","age_c_post_sq"],"dataset":"carpenter_the_minimum_legal","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["over"],"y":"visit_all_np_r"},"attempt":1,"cached":false,"call_id":"call_51b8b40b","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"carpenter_the_minimum_legal":"445d2bbe7bb38003d078f082d967e07cd8383187389dffe2765cc6a38a5ce066"},"decided_by":"model","duration_ms":3.9013330824673176,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"230867312cec66230ca76a91101320d3160424f1bce4490a3ab621c7b736cfb1","llm_name":"infer__ols","output_digest":"b40e5a3e82de526f096de089208b260935a2a2573847548156520e8d85153c15","rationale":"causcibench_metadata_rule/1: rdd","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_51b8b40b","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":80},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":7},{"flag":false,"name":"r2","note":"","value":0.8925098904625572},{"flag":false,"name":"df_resid","note":"","value":73},{"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":223.44381034541217,"ci_level":0.95,"ci_low":102.53458972670578,"derivation":{"note_pt":"","steps":[{"formula":"","result":162.98920003605897,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":80.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":7.0}],"text_pt":"Coeficiente de over na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de visit_all_np_r.","unit":""},{"formula":"ep = \u221aV_jj","result":30.333516051790983,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":920.1221960642613}],"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":162.98920003605897},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.992997125889855},{"note":"","symbol":"ep","unit":"","value":30.333516051790983}],"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 73 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.over","label":"Coefficient on over in the regression of visit_all_np_r","se":30.333516051790983,"unit":"","value":162.98920003605897}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":3948.652903863484,"ci_low":3831.6578002135006,"coef":3890.1553520384923,"p":9.653614663231278e-89,"se":29.351548512079717,"t":132.53663091872264,"term":"Intercept"},{"ci_high":223.44381034541217,"ci_low":102.53458972670578,"coef":162.98920003605897,"p":8.837174535120515e-07,"se":30.333516051790983,"t":5.37323796416392,"term":"over"},{"ci_high":-5.49641613631155,"ci_low":-20.890472380137147,"coef":-13.193444258224348,"p":0.0010409058489956563,"se":3.8620367395041506,"t":-3.4161881794833113,"term":"months_21"},{"ci_high":41.158618537673306,"ci_low":10.643288741769826,"coef":25.900953639721564,"p":0.0011547969909556186,"se":7.655638184194235,"t":3.383252057705189,"term":"dummy21"},{"ci_high":-65.34330930052423,"ci_low":-124.10174323695361,"coef":-94.72252626873892,"p":1.1863728040408033e-08,"se":14.741223951889612,"t":-6.425689384943973,"term":"age_c_sq"},{"ci_high":190.6407036658827,"ci_low":-0.35003114817519076,"coef":95.14533625885376,"p":0.05082366181918291,"se":47.91545665897092,"t":1.985691943541986,"term":"age_c_post"},{"ci_high":128.58105627438363,"ci_low":68.02235865528931,"coef":98.30170746483647,"p":9.838490881307685e-09,"se":15.192871287271776,"t":6.470252107459851,"term":"age_c_post_sq"}]},"tool":"infer.ols","version":"0.1.0","warnings":["dropped as collinear with the other regressors: ['age_c']"]},"result_for_model_ref":"2e5f3d8b9ba99a5e1f88aa5b355db0abeea5d1838e69cee6b2ca8408fe07a67c","result_sha256":"3f41cb718497e4675c87101ee1c1028dbebae85bb08438ce095ad54abd929fbc","run_id":"20261015T171059Z-suite-causcibench_real-scripted-ded01d","seq":2,"synthetic":false,"task_id":"causcibench_real.q054","timestamp":"2026-10-15T17:11:00.767687Z","tool_id":"infer.ols","turn_id":"call_098129b0"}
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