{"attempt":1,"datasets":{"collections_email":{"description_shown":"In a study to determine the causal effect of sending an email reminder on the repayment of debts, a fintech company conducted a random test involving 5000 customers who were late on their payments. Each customer was randomly assigned to either receive an email about negotiating their debt or to be part of a control group that did not receive the email. Data was collected on the amounts paid by the late customers after this intervention. The dataset collections_email.csv contains variables including the amount paid (`payments`), whether the email was sent (`email`), whether the email was opened (`opened`), whether the customer contacted the collections department to negotiate their debt after having received the email (`agreement`), the customer's credit limit before being late (`credit_limit`), and the customer's risk score prior to the delivery of the email (`risk_score`).","file_sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"What is the average treatment effect (ATE) on payments from sending the email reminder to late-paying customers? Please choose the variables to adjust for, conduct linear regression, and round your answer to the nearest hundredth.","question_sha256":"25346fcf62c3be81fd81dec4a989a201d42c86a1582f5f8e3c216e57c53f9440","run_id":"20261015T170037Z-suite-qrdata_socsci-naive-761cb5","seq":0,"skills":[],"task_id":"qrdata_socsci.356","task_sha256":"dadb195d4ec1c5e2490699b4dd895a332d5de12bf773836abb35918683f8839b","timestamp":"2026-10-15T17:00:37.654638Z"}
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{"arguments":{"cluster":null,"controls":[],"dataset":"collections_email","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["email"],"y":"payments"},"attempt":1,"cached":false,"call_id":"call_89209555","card_version":"0.1.0","code_version":"62cdbe0860ad","dataset_digests":{"collections_email":"a87e53659c327a36822b548e6c2de14c0e3818c8173a93b3a13dacdc5e30958d"},"decided_by":"model","duration_ms":1.9381248857825994,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"7b0c0e3117c8d540201f33b668d9067fd874101a3285a274843d8b8abcf22d49","llm_name":"infer__ols","output_digest":"7604665be9c141a2cde63e271872768c1d71f156ce292dcc6429cd67c834aed4","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_89209555","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":5000},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":8.896912247036148e-06},{"flag":false,"name":"df_resid","note":"","value":4998},{"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":5.142518785619038,"ci_level":0.95,"ci_low":-6.38307958988493,"derivation":{"note_pt":"","steps":[{"formula":"","result":-0.6202804021329461,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":5000.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de email na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de payments.","unit":""},{"formula":"ep = \u221aV_jj","result":2.9395456564423768,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":8.640928666309243}],"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":-0.6202804021329461},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9604387416545477},{"note":"","symbol":"ep","unit":"","value":2.9395456564423768}],"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 4998 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.email","label":"Coefficient on email in the regression of payments","se":2.9395456564423768,"unit":"","value":-0.6202804021329461}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":674.087191232288,"ci_low":665.8656760104457,"coef":669.9764336213668,"p":0.0,"se":2.0968559351422424,"t":319.5147660804452,"term":"Intercept"},{"ci_high":5.142518785619038,"ci_low":-6.38307958988493,"coef":-0.6202804021329461,"p":0.8328862462767449,"se":2.9395456564423768,"t":-0.21101233817325651,"term":"email"}]},"tool":"infer.ols","version":"0.1.0","warnings":[]},"result_for_model_ref":"4a56d7c13c1f651860bad9913bf352212fafbeba3148a37e5e4e526f6fed34d3","result_sha256":"cbb49ad65e90e0bd4e87215dc0086512008fc7a38f7e7d915527f76d5c4204da","run_id":"20261015T170037Z-suite-qrdata_socsci-naive-761cb5","seq":2,"synthetic":false,"task_id":"qrdata_socsci.356","timestamp":"2026-10-15T17:00:37.657055Z","tool_id":"infer.ols","turn_id":"call_c8ef7c26"}
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