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trying to load-balance the few-shot a bit more

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mgaughan 2025-05-30 21:45:30 -05:00
parent 225d7f53c8
commit c7448f2fc2
1 changed files with 4 additions and 4 deletions
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models/p1-categorization.py
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@ -12,11 +12,11 @@ olmo = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-1124-7B").to(device)
tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-1124-7B")
#priming prompt
prompt_1 = "For the GIVEN DATA, Please categorize it based on the following numbered characteristics: \n\n 1: YES/NO (Characteristic 1. This is an English language empirical study. English language empirical studies are academic papers written in English that study or analyze evidence. Literature reviews are not empirical studies.) \n 2: YES/NO (Characteristic 2. This focuses on free and open source software (FOSS). The focus of this paper is on FOSS projects and ecosystems.) \n 3: YES/NO (Characteristic 3. This focuses on FOSS project evolution. FOSS project evolution is the study of longitudinal changes to the characteristics of free and open source projects.) \n 4: YES/NO (Characteristic 4. This focuses on FOSS project adaptation. FOSS project adaptation describes the intentional changes made to the characteristics of FOSS projects to better align with the project's broader environment.) \n\n Only respond with the appropriate number followed by 'YES' if the characteristic is present in the provided data or 'NO' if it is not (e.g. '1. NO; 2. YES;'). Do not provide any additional information."
prompt_1 = "For the GIVEN DATA, Please categorize it based on the following numbered characteristics: \n\n 1: YES/NO (Characteristic 1. This is an English language empirical study. English language empirical studies analyze observational or experimental data. We are exlcuding literature reviews from this definition.) \n 2: YES/NO (Characteristic 2. This focuses on free and open source software (FOSS). The focus of this paper is on FOSS projects and ecosystems.) \n 3: YES/NO (Characteristic 3. This focuses on FOSS project evolution. FOSS project evolution is the study of longitudinal changes to the characteristics of free and open source projects.) \n 4: YES/NO (Characteristic 4. This focuses on FOSS project adaptation. FOSS project adaptation describes the intentional changes made to the characteristics of FOSS projects to better align with the project's broader environment.) \n\n Only respond with the appropriate number followed by 'YES' if the characteristic is present in the provided data or 'NO' if it is not (e.g. '1. NO; 2. YES;'). Do not provide any additional information."
example_1 = "Example 1: TITLE - Analysis of Open Source Software Evolution Using Evolution Curve Method \n ABSTRACT - Design and evolution of modem information systems is influenced by many factors: technical, organizational, social, and psychological. This is especially true for open source software systems (OSSS), when many developers from different backgrounds interact, share their ideas and contribute towards the development and improvement of a software product. The evolution of all OSSS is a continuous process of source code development, adaptation, improvement and maintenance. Studying changes to the various characteristics of source code can help us understand the evolution of a software system. In this paper, the software evolution process is analyzed using a proposed Evolution curve (E-curve) method, which is based on information theoretic metrics of source code. The method allows identifying major evolution stages and transition points of an analyzed software system. The application of the E-curves is demonstrated for the eMule system. .\n CATEGORIES: 1. YES; 2. YES; 3.YES; 4. NO"
example_4 = "Example 4: TITLE - Analysis of Open Source Software Evolution Using Evolution Curve Method \n ABSTRACT - Design and evolution of modem information systems is influenced by many factors: technical, organizational, social, and psychological. This is especially true for open source software systems (OSSS), when many developers from different backgrounds interact, share their ideas and contribute towards the development and improvement of a software product. The evolution of all OSSS is a continuous process of source code development, adaptation, improvement and maintenance. Studying changes to the various characteristics of source code can help us understand the evolution of a software system. In this paper, the software evolution process is analyzed using a proposed Evolution curve (E-curve) method, which is based on information theoretic metrics of source code. The method allows identifying major evolution stages and transition points of an analyzed software system. The application of the E-curves is demonstrated for the eMule system. .\n CATEGORIES: 1. YES; 2. YES; 3.YES; 4. NO"
example_4 = "Example 4: TITLE - Thermal Insulation Properties of Milkweed Floss Nonwovens: Influence of Temperature, Relative Humidity, and Fiber Content \n ABSTRACT - This study investigated the influence of fiber content, temperature, and relative humidity on the thermal insulation properties of nonwoven mats made of seed fibers from Asclepias Syriaca, commonly known as milkweed floss. Nonwoven mats with a 1-inch thickness were produced by uniformly arranging milkweed fibers within a mold. Various quantities of fiber were employed to obtain nonwoven mats with a fiber content ranging from 5 to 35 kg/m3. Thermal conductivity and thermal diffusivity were measured across diverse relative humidity levels and temperatures. Simultaneously, milkweed floss samples were exposed to identical environmental conditions to assess the moisture regain and specific heat capacities of the fiber. The specific heat capacity of milkweed and thermal conductivity of the nonwovens exhibited a linear increase with temperature. The thermal diffusivity and thermal conductivity of the nonwovens decreased with rising fiber content. The thermal insulation properties of the nonwovens remained partially stable below 30\\% relative humidity but substantially deteriorated at higher levels. The nonwovens exhibited optimal thermal insulation properties at a fiber content between 20 and 25 kg/m3. The results of this study highlighted several technical advantages of employing milkweed floss as a sustainable and lightweight solution for thermal insulation. \n CATEGORIES: 1. YES; 2. NO; 3. NO; 4. NO;"
example_1 = "Example 1: TITLE - Thermal Insulation Properties of Milkweed Floss Nonwovens: Influence of Temperature, Relative Humidity, and Fiber Content \n ABSTRACT - This study investigated the influence of fiber content, temperature, and relative humidity on the thermal insulation properties of nonwoven mats made of seed fibers from Asclepias Syriaca, commonly known as milkweed floss. Nonwoven mats with a 1-inch thickness were produced by uniformly arranging milkweed fibers within a mold. Various quantities of fiber were employed to obtain nonwoven mats with a fiber content ranging from 5 to 35 kg/m3. Thermal conductivity and thermal diffusivity were measured across diverse relative humidity levels and temperatures. Simultaneously, milkweed floss samples were exposed to identical environmental conditions to assess the moisture regain and specific heat capacities of the fiber. The specific heat capacity of milkweed and thermal conductivity of the nonwovens exhibited a linear increase with temperature. The thermal diffusivity and thermal conductivity of the nonwovens decreased with rising fiber content. The thermal insulation properties of the nonwovens remained partially stable below 30\\% relative humidity but substantially deteriorated at higher levels. The nonwovens exhibited optimal thermal insulation properties at a fiber content between 20 and 25 kg/m3. The results of this study highlighted several technical advantages of employing milkweed floss as a sustainable and lightweight solution for thermal insulation. \n CATEGORIES: 1. YES; 2. NO; 3. NO; 4. NO;"
example_3 = "Example 3: TITLE - Social network structures in open source software development teams \n ABSTRACT - Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects move forward.\n CATEGORIES: 1. YES; 2. YES; 3. NO; 4. NO"
@ -28,7 +28,7 @@ with open("cites/053025_man_filtered_dedup.csv", mode='r', newline='') as file:
index = -1
for row in reader:
index += 1
if index < 0:
if index <= 0:
continue
cite_dict = {}
#organizing the data from each citation