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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'dataset_info', 'pretty_name'}) and 3 missing columns ({'prefix', 'input', 'target'}).

This happened while the json dataset builder was generating data using

hf://datasets/fine123/Citrus_S3/metadata.json (at revision ede9de6d64103475b9622a2ef80a181d02dcd13d), [/tmp/hf-datasets-cache/medium/datasets/77753074608265-config-parquet-and-info-fine123-Citrus_S3-6362048f/hub/datasets--fine123--Citrus_S3/snapshots/ede9de6d64103475b9622a2ef80a181d02dcd13d/data/Citrus_S3.jsonl (origin=hf://datasets/fine123/Citrus_S3@ede9de6d64103475b9622a2ef80a181d02dcd13d/data/Citrus_S3.jsonl), /tmp/hf-datasets-cache/medium/datasets/77753074608265-config-parquet-and-info-fine123-Citrus_S3-6362048f/hub/datasets--fine123--Citrus_S3/snapshots/ede9de6d64103475b9622a2ef80a181d02dcd13d/metadata.json (origin=hf://datasets/fine123/Citrus_S3@ede9de6d64103475b9622a2ef80a181d02dcd13d/metadata.json)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              pretty_name: string
              dataset_info: struct<config_name: string, data_files: list<item: string>>
                child 0, config_name: string
                child 1, data_files: list<item: string>
                    child 0, item: string
              to
              {'prefix': Value('string'), 'input': Value('string'), 'target': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'dataset_info', 'pretty_name'}) and 3 missing columns ({'prefix', 'input', 'target'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/fine123/Citrus_S3/metadata.json (at revision ede9de6d64103475b9622a2ef80a181d02dcd13d), [/tmp/hf-datasets-cache/medium/datasets/77753074608265-config-parquet-and-info-fine123-Citrus_S3-6362048f/hub/datasets--fine123--Citrus_S3/snapshots/ede9de6d64103475b9622a2ef80a181d02dcd13d/data/Citrus_S3.jsonl (origin=hf://datasets/fine123/Citrus_S3@ede9de6d64103475b9622a2ef80a181d02dcd13d/data/Citrus_S3.jsonl), /tmp/hf-datasets-cache/medium/datasets/77753074608265-config-parquet-and-info-fine123-Citrus_S3-6362048f/hub/datasets--fine123--Citrus_S3/snapshots/ede9de6d64103475b9622a2ef80a181d02dcd13d/metadata.json (origin=hf://datasets/fine123/Citrus_S3@ede9de6d64103475b9622a2ef80a181d02dcd13d/metadata.json)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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prefix
string
input
string
target
string
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You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 42-year-old man with non-small cell lung cancer is enrolled in a clinical trial for a new chemotherapeutic drug. ...
<think> The microtubule network plays a crucial role in various cellular processes, especially during cell division or mitosis. Microtubules are dynamic structures composed of alpha (α) and beta (β) tubulin dimers that constantly undergo phases of polymerization (assembly) and depolymerization (disassembly). This dynam...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Tom bought a new bicycle for $80. After 4 years of use, he sold it to a second-hand dealer for $15. What was the an...
<answer> To determine the annual depreciation and the annual rate of depreciation for Tom's bicycle using the straight-line method, we'll follow these steps: **1. Calculate the Total Depreciation** The total depreciation is the difference between the original cost of the asset and its salvage value (the value at the...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 22-year-old woman suffered a scald injury from boiling water to her right hand and forearm one hour ago. Physical...
<think> Assessing the depth and severity of a burn injury involves a systematic evaluation of the clinical presentation and estimating the total body surface area (TBSA) affected. Let's analyze the patient's condition step by step. **1. Determining the Depth of the Burn:** Burns are classified based on the depth of t...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 33-year-old woman comes to the physician because of a 4-day history of fever and neck pain that radiates to the j...
<think> The most likely diagnosis for this 33-year-old woman is **subacute thyroiditis**. Let's analyze the clinical presentation and laboratory findings to understand why this is the case. **Clinical Presentation:** - **Fever and Neck Pain:** She has a 4-day history of fever and neck pain radiating to the jaw and ea...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 25-year-old male presents with abdominal pain, diarrhea, and a fever of 38.7°C. After 6 days of treatment, the sy...
<think> In evaluating this patient's presentation, a systematic approach considering the timeline of symptoms, clinical findings, and diagnostic results is essential to arrive at the most appropriate diagnosis. **Initial Presentation and Antecedent Event:** The patient is a 25-year-old male who initially experienced ...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Tibialis posterior is inseed in all the tarsal bones, except: Please explain which tarsal bone is not included in t...
<think> To explain which tarsal bone is not included in the insertion of the tibialis posterior, it's important to explore the anatomy and attachment points of this muscle. The tibialis posterior is a key muscle in the deep posterior compartment of the leg, playing a crucial role in maintaining the stability of the med...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Acantholysis is seen in all except Could you explain in which conditions acantholysis is not observed? </Question>...
<answer> Acantholysis refers to the loss of intercellular connections, specifically desmosomes, between keratinocytes in the epidermis. This loss leads to the separation of keratinocytes and the formation of intraepidermal blisters or vesicles. Understanding where acantholysis occurs helps in diagnosing and differenti...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Two weeks after being hospitalized for acute pancreatitis, a 36-year-old man comes to the physician for a follow-up...
<think> Gemfibrozil is a medication belonging to the fibrate class, widely used for its lipid-lowering effects, particularly on triglycerides. To determine its expected beneficial effect in this patient, it's essential to understand both the patient's condition and the mechanism of action of gemfibrozil. The patient i...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 19-year-old man comes to the physician for the evaluation of progressive difficulty climbing stairs over the last...
<think> To determine the most appropriate next step to confirm the diagnosis in this 19-year-old man, we need to carefully analyze his clinical presentation and laboratory findings. **Clinical Presentation:** - **Age and Gender:** A 19-year-old man. - **Symptoms:** Progressive difficulty climbing stairs over the past...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Of the following statements, which one is incorrect? Please explain your answer. </Question> Please begin your res...
<answer> The incorrect statement is: **"Biotransformation refers to the oxidation of drugs."** **Explanation:** Biotransformation is the process by which the body chemically modifies substances, including drugs. While oxidation is one type of biotransformation reaction, it is not the only one. Biotransformation encom...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> 下列哪项是H+泵抑制药?(  ) 请描述H+泵抑制药的例子。 </Question> Please begin your response. The formatted output should be as follows:...
<think> 在药理学领域,H⁺泵抑制剂,也称为质子泵抑制剂(Proton Pump Inhibitors,PPIs),在治疗胃酸相关疾病中发挥着重要作用。这些药物通过抑制胃壁细胞上的H⁺/K⁺ ATP酶,即质子泵,来减少胃酸的分泌。质子泵是胃酸分泌过程中的关键步骤,抑制它可以显著降低胃酸的产生。 常见的H⁺泵抑制剂包括以下几种: 首先,**奥美拉唑**是最早上市的质子泵抑制剂。它通过与质子泵的巯基形成共价键,非竞争性、不可逆地抑制质子泵的活性,从而有效地抑制胃酸分泌。 其次,**兰索拉唑**也是一种常用的质子泵抑制剂,同样通过抑制质子泵来减少胃酸的分泌。它在生物利用度和起效时间上可能有所不同,提供了不同的治疗选择。 再次...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> 弧菌主要分布在(  )。请描述弧菌的主要分布区域。 </Question> Please begin your response.
<answer> 弧菌是一类革兰氏阴性、呈弧形的杆状细菌,广泛存在于自然界中。为了了解弧菌的主要分布区域,我们需要从其生存环境和生态特点入手。 首先,弧菌是嗜盐微生物,适宜在一定盐度的环境中生存。它们常见于海洋环境中,特别是沿海和近海的温暖海域。在这些区域,水温较高,盐度适中,营养物质丰富,为弧菌的繁殖提供了理想条件。 其次,弧菌也存在于河口和咸淡水区域。这些地方是淡水和海水的交汇处,盐度变化多样,弧菌能够适应这种盐度的波动。此外,在受污染的水体中,如因人类活动而富含有机物的水域,弧菌也能大量繁殖。 另外,弧菌还与水生生物密切相关。它们可以附着在鱼类、贝类和其他海洋生物的表面或体内,这些生物既是弧菌的宿主,也是传播媒介。 综...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> All of the following are features of Millard Gubler Syndrome, Except : What are the features of Millard Gubler Sy...
<answer> Millard-Gubler Syndrome is a neurological condition resulting from a lesion in the ventral portion of the pons, specifically affecting certain cranial nerves and neural pathways. It is important to distinguish the characteristic features of this syndrome to accurately diagnose and differentiate it from other ...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Which hepatitis causes more morbidity in pregnant female? Please answer this question. </Question> Please begin yo...
<answer> The type of hepatitis that causes more morbidity in pregnant females is **Hepatitis E**. This can be understood by examining the characteristics and impacts of the different hepatitis viruses during pregnancy. Firstly, there are five main types of viral hepatitis: A, B, C, D, and E. Each type affects the body...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A homebuyer wishes to take out a mortgage of $100,000 for a 30-year period. What monthly payment is required if the...
<think> To determine the monthly payment required for a $100,000 mortgage over a 30-year period with an annual interest rate of 9%, we can use the standard formula for calculating the monthly payment on a fixed-rate mortgage. This formula accounts for the principal amount, the monthly interest rate, and the total numbe...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> At what value of Z would the innermost orbit be expected to be pulled inside a nucleus of radius 1.0 × 10^-13 cm, a...
<think> To determine the value of \( Z \) at which the innermost orbit (\( n = 1 \)) would be expected to be pulled inside a nucleus of radius \( r_{\text{nucleus}} = 1.0 \times 10^{-13} \) cm, we can utilize the Bohr model of the atom. The Bohr model provides a foundational approach to understanding the atomic structu...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> A 38-year-old woman comes to the physician because of a 3-month history of moderate abdominal pain that is unrespon...
<think> To determine what further evaluation is likely to reveal in this patient, let's carefully analyze her clinical presentation. **Key Clinical Features:** 1. **Moderate Abdominal Pain**: She has been experiencing abdominal pain for three months that is unresponsive to medication. Persistent abdominal pain can be...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Thomas Sidencarries property-damage insurance on his car with a limit of $5,000. He damages Frank Hartman's car in ...
<think> To determine how much Thomas Siden's insurance company will pay for the damages to Frank Hartman's car, we need to understand how property-damage liability insurance works and apply it to the given situation. **1. Property-Damage Liability Coverage:** - **Coverage Limit:** Thomas has property-damage liability...
You are an expert with extensive experience in medical research and clinical practice, and you are needed to assist users in answering questions related to medical issues. Let's think step by step.
You are tasked with addressing a medical examination question. Please carefully read the question, provide a detailed thought process, and then present your final answer. Here is the question: <Question> Please carefully read the following question, which is prepared in a closed-choice question format (although there ...
<think> 要回答关于局部兴奋特征中哪一项是错误的问题,首先需要理解局部兴奋的概念和其主要特征。 **局部兴奋**(也称为局部电位或级电位)是指细胞膜在受到刺激后产生的局部电位变化,这种变化不一定达到触发动作电位的阈值。局部兴奋在神经信号传递的初始阶段起着关键作用。 局部兴奋的主要特征包括: 1. **幅度与刺激强度成比例**:局部兴奋的幅度会随着刺激强度的增加而增大,即表现出**级性反应**。这意味着刺激越强,膜电位的变化就越大。 2. **衰减性传导**:局部兴奋在沿着细胞膜传播时,其幅度会随着距离的增加而减小。这表示电位变化会在远离刺激点的地方逐渐减弱,不能长距离传播。 3. **可加成性**:局部兴奋可以通过*...
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Citrus: Leveraging Expert Cognitive Pathways in a Medical Language Model for Advanced Medical Decision Support

📑Paper🤗Github Page🤗Model📚Medical Reasoning Data📚Evaluation Data

The Introduction to Our Work

1. Main approaches

image

2. Overview of training stages and training data pipeline

Citrus is a medical language model that bridges the gap between clinical expertise and AI reasoning by emulating the cognitive processes of medical experts. The model is trained on a large corpus of simulated expert disease reasoning data in sft-stage-3, synthesized using a novel approach that accurately captures the decision-making pathways of clinicians.

The contributions of this work are as follows:

  1. We propose a training-free reasoning approach that emulates the cognitive processes of medical experts, enabling large language models to enhance their medical capabilities in clinical diagnosis and treatment.

  2. In conjunction with the data construction method, we introduce a multi-stage post-training approach to further improve the model’s medical performance.

  3. We have made the Citrus model and its training data publicly available as open-source resources to advance research in AI-driven medical decision-making.

  4. We have developed and open-sourced a large-scale, updatable clinical practice evaluation dataset based on real-world data, accurately reflecting the distribution of patients in real-world settings.

In our work, we provide detailed insights into Citrus, covering its model architecture, dataset, and code. We are releasing Citrus_S3, the supervised fine-tuning (SFT) data for stage 3, which comprises 20,000 samples. We hope that our contributions will foster progress within the community in advancing the capabilities of large models.

The Introduction to Citrus_S3

  1. Data Construction: The Citrus_S3 dataset is designed to enhance the medical reasoning abilities of large language models (LLMs). It contains 20,000 long Chain-of-Thought (COT) data points, which we utilize to improve medical reasoning capabilities in sft-stage-3. The dataset is derived from approximately 100,000 medical benchmark problems with verified ground truth answers. To ensure data quality and diversity, we employ several advanced data processing techniques, outlined below:

    1. Collect Question Seeds: We gather a wide range of complex medical questions that are sufficiently intricate to stimulate the reasoning process and are accompanied by properly verified ground truth answers.

    2. Query Rewriting: To enable the model to genuinely learn reasoning skills and improve generalization, rather than merely answering closed-ended questions, we convert all collected multiple-choice questions into open-ended question formats.

    3. Construct Answers Using the Dual-Expert Method: The answers in the training data are synthesized using our dual-expert method, which ensures that the model generates a reasonable and accurate reasoning process. We adapt the training-free method by providing the reflection model with the ground truth for the medical questions encountered by the reasoning model. The reflection model evaluates the reasonableness of the steps generated by the reasoning model and subtly guides it toward the correct answer without directly providing the solution. This approach redefines step 4 in the dual-expert method.

  2. Data Format: The Citrus_S3 dataset follows a general template format: <sft-input, sft-target>. The sft-input consists of open-ended questions, and we expect the reasoning model to follow a structured thought process before providing answers. The resulting sft-target outputs follow the format: <think>thinking tokens<think> <answer>answer tokens</answer>, where the reasoning process is contained within <think> and the final conclusion is given in <answer>.

  3. Data Path: Citrus_S3.jsonl

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