{"call_id":"call_2a68e21c","run_id":"20261015T171234Z-suite-nist_anova-baseline-71784e/nist_anova.smls02.tool/e1a1","step":"data","kind":"note","name":"data.transform","version":"","code_version":"2925aeab2262","inputs":{"dataset":"d","index":0,"op":"dummies","args":{"column":"treatment","prefix":"treatment","drop_first":true}},"input_digest":"","dataset_digests":{},"result":null,"outputs":{"rows_before":1809,"rows_after":1809,"frame_sha256_before":"6cb2bb68727fb7574ad811ffd09792f441edb5beb665e6471c627c3d9e84c785","frame_sha256_after":"40265bb6a4240c34fa765dd90a3fe6242ebe37ae0ae601c4865ceef0c45d0cd1"},"output_digest":"","params_versions":[],"sources":[],"started_at":"2026-10-15T17:12:34.461411Z","duration_ms":0.5824998952448368,"error":null,"decided_by":"code","rationale":"","cached":false,"informed_by":[],"model":null,"prompt":null,"response":null,"tokens_in":null,"tokens_out":null,"meta":{}}
{"call_id":"call_d928a647","run_id":"20261015T171234Z-suite-nist_anova-baseline-71784e/nist_anova.smls02.tool/e1a1","step":"analysis","kind":"tool","name":"infer.linear_hypothesis","version":"0.1.0","code_version":"2925aeab2262","inputs":{"dataset":"d","y":"response","x":["treatment_2","treatment_3","treatment_4","treatment_5","treatment_6","treatment_7","treatment_8","treatment_9"],"hypothesis":"treatment_2 = 0, treatment_3 = 0, treatment_4 = 0, treatment_5 = 0, treatment_6 = 0, treatment_7 = 0, treatment_8 = 0, treatment_9 = 0","cluster":null,"se":"classical","subset":null},"input_digest":"d9ac946eac7ed4017b491543734b9be5b075b0a8da2ae4dabbdd79d85f56b823","dataset_digests":{"d":"40265bb6a4240c34fa765dd90a3fe6242ebe37ae0ae601c4865ceef0c45d0cd1"},"result":{"tool":"infer.linear_hypothesis","version":"0.1.0","call_id":"call_d928a647","status":"ok","reason":"","figures":[{"key":"F","value":200.9999999999995,"unit":"","label":"F statistic of treatment_2 = 0; treatment_3 = 0; treatment_4 = 0; treatment_5 = 0; treatment_6 = 0; treatment_7 = 0; treatment_8 = 0; treatment_9 = 0","se":null,"ci_low":null,"ci_high":null,"ci_level":null,"derivation":{"steps":[{"text_pt":"Estatística de Wald das 8 restrições, com a covariância classical (homoskedastic) standard errors.","formula":"","terms":[{"symbol":"m","value":8.0,"unit":"restrições","note":""}],"result":1607.999999999996,"unit":""},{"text_pt":"Estatística F: a de Wald dividida pelo número de restrições.","formula":"F = W / m","terms":[{"symbol":"W","value":1607.999999999996,"unit":"","note":""},{"symbol":"m","value":8.0,"unit":"restrições","note":""}],"result":200.9999999999995,"unit":""}],"note_pt":""}},{"key":"p_value","value":4.037141885758291e-243,"unit":"probability","label":"p-value of treatment_2 = 0; treatment_3 = 0; treatment_4 = 0; treatment_5 = 0; treatment_6 = 0; treatment_7 = 0; treatment_8 = 0; treatment_9 = 0","se":null,"ci_low":null,"ci_high":null,"ci_level":null,"derivation":{"steps":[{"text_pt":"Probabilidade de uma F(8, 1800) exceder a estatística observada.","formula":"","terms":[],"result":4.037141885758291e-243,"unit":"probabilidade"}],"note_pt":""}}],"diagnostics":[{"name":"statistic","value":"F","flag":false,"note":"F = W/m against F(m, n − k)"},{"name":"df_numerator","value":8,"flag":false,"note":"number of restrictions"},{"name":"df_denominator","value":1800,"flag":false,"note":"residual degrees of freedom n − k"},{"name":"se_type","value":"classical","flag":false,"note":"classical (homoskedastic) standard errors"},{"name":"n_obs","value":1809,"flag":false,"note":""},{"name":"n_clusters","value":null,"flag":false,"note":"errors not clustered"}],"tables":{"restrictions":[{"restriction":"treatment_2 = 0","estimate":-0.10000000000000009,"hypothesized":0.0},{"restriction":"treatment_3 = 0","estimate":0.09999999999999998,"hypothesized":0.0},{"restriction":"treatment_4 = 0","estimate":-0.10000000000000009,"hypothesized":0.0},{"restriction":"treatment_5 = 0","estimate":0.09999999999999998,"hypothesized":0.0},{"restriction":"treatment_6 = 0","estimate":-0.10000000000000009,"hypothesized":0.0},{"restriction":"treatment_7 = 0","estimate":0.09999999999999998,"hypothesized":0.0},{"restriction":"treatment_8 = 0","estimate":-0.10000000000000009,"hypothesized":0.0},{"restriction":"treatment_9 = 0","estimate":0.09999999999999998,"hypothesized":0.0}],"coefficients":[{"term":"Intercept","coef":1.4,"se":0.007053456158586019,"t":198.48425630260851,"p":0.0,"ci_low":1.3861661778643664,"ci_high":1.4138338221356335},{"term":"treatment_2","coef":-0.10000000000000009,"se":0.009975093361076447,"t":-10.024968827881601,"p":4.7048753115723204e-23,"ci_low":-0.1195639788836703,"ci_high":-0.08043602111632987},{"term":"treatment_3","coef":0.09999999999999998,"se":0.009975093361076453,"t":10.024968827881585,"p":4.704875311573031e-23,"ci_low":0.08043602111632975,"ci_high":0.11956397888367021},{"term":"treatment_4","coef":-0.10000000000000009,"se":0.009975093361076319,"t":-10.024968827881729,"p":4.704875311566536e-23,"ci_low":-0.11956397888367006,"ci_high":-0.08043602111633012},{"term":"treatment_5","coef":0.09999999999999998,"se":0.009975093361076279,"t":10.024968827881759,"p":4.7048753115651787e-23,"ci_low":0.0804360211163301,"ci_high":0.11956397888366986},{"term":"treatment_6","coef":-0.10000000000000009,"se":0.00997509336107639,"t":-10.024968827881658,"p":4.7048753115697243e-23,"ci_low":-0.1195639788836702,"ci_high":-0.08043602111632998},{"term":"treatment_7","coef":0.09999999999999998,"se":0.00997509336107638,"t":10.024968827881658,"p":4.7048753115697243e-23,"ci_low":0.08043602111632989,"ci_high":0.11956397888367007},{"term":"treatment_8","coef":-0.10000000000000009,"se":0.009975093361076343,"t":-10.024968827881706,"p":4.704875311567541e-23,"ci_low":-0.1195639788836701,"ci_high":-0.08043602111633008},{"term":"treatment_9","coef":0.09999999999999998,"se":0.00997509336107632,"t":10.024968827881716,"p":4.704875311567068e-23,"ci_low":0.08043602111633001,"ci_high":0.11956397888366994}]},"datasets":{},"warnings":[],"assumptions":["errors are independent and have the same variance for every observation"],"notes":""},"outputs":null,"output_digest":"5e57dc970d65449a9f30a4a04beb6faa44eac37137fe51d05eea48e2b27776e8","params_versions":[],"sources":[],"started_at":"2026-10-15T17:12:34.464990Z","duration_ms":5.976499989628792,"error":null,"decided_by":"code","rationale":"","cached":false,"informed_by":[],"model":null,"prompt":null,"response":null,"tokens_in":null,"tokens_out":null,"meta":{}}
