DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data | Paper Citation Record

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data gpt-oss-120b & gpt-oss-20b Model Card

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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This paper cites Evaluating Large Language Models Trained on Code.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Evaluating Large Language Models Trained on Code

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data The Llama 3 Herd of Models

Reference 14

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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This paper cites Hoos, and Kevin Leyton-Brown.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Hoos, and Kevin Leyton-Brown

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 21

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data GPT-4 Technical Report

Reference 22

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Interpolation-Prediction Networks for Irregularly Sampled Time Series

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Multi-Time Attention Networks for Irregularly Sampled Time Series

Reference 29

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Hoos, and Kevin Leyton-Brown

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Self-Consistency Improves Chain of Thought Reasoning in Language Models

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data ReAct: Synergizing Reasoning and Acting in Language Models

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Do not include any meta commentary, rationale, or explanations

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Do NOT introduce, infer, assume, or add any information that is not explicitly present in the input notes

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Preserve information that is most useful for future optimiza- tion decisions:

Reference 50

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data System Prompt for Evaluator You are an expert clinical ML engineer and code reviewer acting as an evaluator for an agentic machine learning system

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data The raw datasets have exactly the same feature space

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data If exists, You must strictly avoid any feature engineering or preprocessing oper- ation that uses, derives from, or is conditioned on the target label

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Keep ID ({id_col})/Label ({la- bel_col})/Time ({time_col}) column names and case unchanged

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

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DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data In-code Requirements:

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.816138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 691f80ea-51bf-4681-8b98-27cfa69244c7 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.800669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4595d5d3-415b-4f38-a032-f637fcee2ec9 · outbound

This paper cites The datasets have exactly the same feature space.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data The datasets have exactly the same feature space

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.726184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d42df0b2-085f-493f-8a3f-49c37fee3e1f · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.711308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20091e6a-1f1c-412a-864a-fff4eab70397 · outbound

This paper cites test_performance (a single float value reporting the best model test performance), and (iv) best_model (ONLY hyperparameters and name of the best model).

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data test_performance (a single float value reporting the best model test performance), and (iv) best_model (ONLY hyperparameters and name of the best model)

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.696555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f9d620fd-e483-4f14-af3e-9a535d262f09 · outbound

This paper cites If all models failed, output empty CSV), and save as a csv file to shap_csv_path with two columns:.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data If all models failed, output empty CSV), and save as a csv file to shap_csv_path with two columns:

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.680782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1b2847cb-192e-4a63-98c6-85ed72a3a949 · outbound

This paper cites abs_mean_shap (the mean value of absolute SHAP), the CSV file should be ordered by descending abs_mean_shap.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data abs_mean_shap (the mean value of absolute SHAP), the CSV file should be ordered by descending abs_mean_shap

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.664796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0ed63831-c5e7-412c-9dfd-c288a99d7d1c · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.649685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f707574-2e01-4a17-95b9-2c9f851aaa37 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.634440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d7f33ca0-dc40-42e6-aed3-b7daaa9ce26d · outbound

This paper cites accuracy.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data accuracy

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.617718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd85190a-42c2-4037-af6a-65cd97b04551 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.602160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2df53e46-414b-468b-84fb-f6bf24e0ded3 · outbound

This paper cites The same preprocessing strategy should not be blindly applied to all features.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data The same preprocessing strategy should not be blindly applied to all features

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.587033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 54586803-be5c-4ec5-98b0-738171ad7621 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.571101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 78d40fa3-e6cc-40f4-a69b-929b2f87412e · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.556036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcbb27a3-3744-4372-9894-507bcea9d354 · outbound

This paper cites IMPORTANT: DO NOT use ‘xgboost‘ or ‘lightgbm‘.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data IMPORTANT: DO NOT use ‘xgboost‘ or ‘lightgbm‘

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.541133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0008bf66-0d1b-4f9c-bc97-16dbbe900224 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.526355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd4109a0-35de-4bda-976e-c7c40ed537cd · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.510817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 14e0bfed-70ae-4bb2-b431-4ef22e0ba9cf · outbound

This paper cites Invalid",.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Invalid",

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.496004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 72edfe27-4047-4347-8419-706eb9b9ebe2 · outbound

This paper cites intended.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data intended

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.481199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6a796b95-fde0-4a63-ae15-bf46ccc61139 · outbound

This paper cites set to NaN).

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data set to NaN)

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.466487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 34aec5e8-f9ec-4aff-b9c9-f29a89074deb · outbound

This paper cites This dataset historically contains ‘un- known” encodings (e.g., -1) (you even saw Mpoc_-1 show up in Step 6 SHAP).

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data This dataset historically contains ‘un- known” encodings (e.g., -1) (you even saw Mpoc_-1 show up in Step 6 SHAP)

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.452216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d0076119-5774-406d-a662-b0eb74f395ef · outbound

This paper cites days-to-start.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data days-to-start

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.436596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 369676e5-c23a-4488-8250-9d815262d5ef · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.421837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bf396bf8-b4fa-4320-808e-376b5f8175a0 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.407150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9e2585c3-eefb-4f81-a364-94885662cd85 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.392917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c1d9de9-48cf-456c-8b07-9aba7ffa1830 · outbound

This paper cites an unresolved cited work.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:22:31.379337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f6160493-3b57-4738-99bd-8ae0f0adc11d · outbound

This paper cites If you implement only one change: fix anchoring so you’re not static-only for∼95% of patients—that’s the bottleneck cur- rently limiting validation AUROC.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data If you implement only one change: fix anchoring so you’re not static-only for∼95% of patients—that’s the bottleneck cur- rently limiting validation AUROC

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.365205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3d978824-13be-4ad2-ba7c-71bac151ec0e · outbound

This paper cites static-only.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data static-only

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.350418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0ad00f6e-12db-4ae6-ab8b-8a4a15c49f0c · outbound

This paper cites Change * Always populate meds/comorbidities from the chosen “base” row (or any available row), even if anchor is uncertain.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Change * Always populate meds/comorbidities from the chosen “base” row (or any available row), even if anchor is uncertain

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.335077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f13522d8-3e28-4558-9ace-ceb2914b13b7 · outbound

This paper cites un- known/other.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data un- known/other

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.320473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0095a66d-604f-42ec-b8f5-c8d89e624c05 · outbound

This paper cites So those bins never enter feature_cols.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data So those bins never enter feature_cols

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.306629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1f2ed56f-1ac5-4582-b78c-455a07acb8f2 · outbound

This paper cites everything missing→ everything pruned.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data everything missing→ everything pruned

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.292752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c0113c6c-1945-4902-a77c-00a44bb269ec · outbound

This paper cites That can happen when clinical disease activity features are missing, but it can also reflect proxy learning that doesn’t validate well.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data That can happen when clinical disease activity features are missing, but it can also reflect proxy learning that doesn’t validate well

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.278811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 00d5a406-882c-4b38-9739-42ae5f0075d6 · outbound

This paper cites usable longitudi- nal coverage.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data usable longitudi- nal coverage

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.264544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aa252ed1-6495-4331-8b5a-8482b68a3213 · outbound

This paper cites Keep broad coverage, but reject anchors that imply impossible timelines.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data Keep broad coverage, but reject anchors that imply impossible timelines

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.250590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ef127ee-674e-4ea8-9f10-ef14a0867c55 · outbound

This paper cites always missing.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data always missing

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.235965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 52664e12-ebd0-4c4a-a1e1-63a5d01578e8 · outbound

This paper cites has_any_measurement.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data has_any_measurement

Reference 102

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.222058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a480c445-cc47-4303-b258-9bd60f95c33f · outbound

This paper cites model-ready.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data model-ready

Reference 103

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.207714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dc457961-c135-4131-888d-504b80deb773 · outbound

This paper cites structurally missing.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data structurally missing

Reference 104

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.193894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f26c2eca-08c2-40c3-9aa3-e0b4883ff25b · outbound

This paper cites * Try no KBest for LR and rely on ridge/elasticnet regulariza- tion (much more stable in p>>n).

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data * Try no KBest for LR and rely on ridge/elasticnet regulariza- tion (much more stable in p>>n)

Reference 105

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.179303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5eec8b4-aedd-4450-89b9-90e9a377b4d8 · outbound

This paper cites * Your step history already found useful solutions at C≈3 (Step 6), but Step 7’s search tops out at C=0.3 for L2 and elastic.

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data * Your step history already found useful solutions at C≈3 (Step 6), but Step 7’s search tops out at C=0.3 for L2 and elastic

Reference 106

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:22:31.163450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers