PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language | Paper Citation Record

Observation a2ec28d7-6270-4dd0-ad33-bc8e518c2b07 · outbound

This paper cites Recent improvements of the particle and heavy ion transport code system—PHITS version 3.33.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Recent improvements of the particle and heavy ion transport code system—PHITS version 3.33

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02ce4a4b-15f0-4585-b5da-7486e31b0fec · outbound

This paper cites MCNP version 6.2 release notes.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language MCNP version 6.2 release notes

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 293cf11b-73e8-4b70-844b-e12dde132c5c · outbound

This paper cites GEANT4—a simulation toolkit.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language GEANT4—a simulation toolkit

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9985ea9a-af1b-4075-89c8-2bea58df31a7 · outbound

This paper cites FLUKA: A multi-particle transport code (program version 2005).

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language FLUKA: A multi-particle transport code (program version 2005)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e73e0443-d4dd-457b-ba88-fb90ae8f41e3 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Evaluating Large Language Models Trained on Code

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70ce1b01-f659-4acd-a1f2-7c2ae610a75a · outbound

This paper cites SWE-bench: Can language models resolve real-world GitHub issues? In: The Twelfth International Conference on Learning Representations (ICLR); 2024.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language SWE-bench: Can language models resolve real-world GitHub issues? In: The Twelfth International Conference on Learning Representations (ICLR); 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a223f2aa-f381-4e21-a30c-4fe3f3136a0c · outbound

This paper cites DS-1000: A natural and reliable benchmark for data science code generation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language DS-1000: A natural and reliable benchmark for data science code generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5369fd8b-2fd5-402d-bcdb-0abf8cf82d51 · outbound

This paper cites Invited paper: VerilogEval: Evaluating large language models for Verilog code generation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Invited paper: VerilogEval: Evaluating large language models for Verilog code generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3883d4ff-e314-4fe0-b238-3c68cd20ddf9 · outbound

This paper cites BigCodeBench: Benchmarking code generation with diversefunctioncallsandcomplexinstructions.In:TheThirteenthInternationalConference on Learning Representations (ICLR); 2025.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language BigCodeBench: Benchmarking code generation with diversefunctioncallsandcomplexinstructions.In:TheThirteenthInternationalConference on Learning Representations (ICLR); 2025

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa598f56-4dc0-4f3f-9aff-e2ffed2d9ebc · outbound

This paper cites SciCode: A research coding benchmark curated by scientists.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language SciCode: A research coding benchmark curated by scientists

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f6db513-5eb9-4a35-bcd9-d5a82776a6fe · outbound

This paper cites Automating Monte Carlo simulations in nuclear engineering with domain knowledge-embedded large language model agents.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Automating Monte Carlo simulations in nuclear engineering with domain knowledge-embedded large language model agents

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eb98e7c-860f-4f57-8b52-c03e7e3daef8 · outbound

This paper cites A self-correcting multi-agent LLM framework for language-based physics simulation and explanation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language A self-correcting multi-agent LLM framework for language-based physics simulation and explanation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c8c1575-97e9-4691-aea3-c6f60217f7e0 · outbound

This paper cites Evaluating the performance of large language 19 models for geometry and simulation file generation in physics-based simulations.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Evaluating the performance of large language 19 models for geometry and simulation file generation in physics-based simulations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac238909-decc-4a99-a2c3-24d9646e5dd7 · outbound

This paper cites OpenFOAMGPT: A retrieval-augmented large language model (LLM) agent for OpenFOAM-based computational fluid dynamics.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language OpenFOAMGPT: A retrieval-augmented large language model (LLM) agent for OpenFOAM-based computational fluid dynamics

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26279d89-94a5-495a-8f10-c49953b0e576 · outbound

This paper cites MetaOpenFOAM: an LLM-based multi-agent framework for CFD.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language MetaOpenFOAM: an LLM-based multi-agent framework for CFD

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db51d044-e521-49b4-9d6e-8d9f7dd0fb6b · outbound

This paper cites CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47064579-345f-4d28-9dce-f5a7b2285cb4 · outbound

This paper cites MooseAgent: A LLM based multi-agent framework for automating MOOSE simulation ; 2025.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language MooseAgent: A LLM based multi-agent framework for automating MOOSE simulation ; 2025

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ade3ced7-7bf8-49f6-8c9c-45359b431a77 · outbound

This paper cites AutoSAM: an agentic framework for automating input file generation for the SAM code with multi-modal retrieval-augmented generation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language AutoSAM: an agentic framework for automating input file generation for the SAM code with multi-modal retrieval-augmented generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcf21966-a402-4969-a9e8-e9c892463ce2 · outbound

This paper cites an unresolved cited work.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b838f9c-ea72-49c4-99a7-ddd74b777c1e · outbound

This paper cites SIMCODE: A Benchmark for Natural Language to ns-3 Network Simulation Code Generation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language SIMCODE: A Benchmark for Natural Language to ns-3 Network Simulation Code Generation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44b8a582-24c6-44dd-aa3c-ad2baa6257cd · outbound

This paper cites Evaluating LLM-generated code for domain-specific languages: molecular dynamics with LAMMPS.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Evaluating LLM-generated code for domain-specific languages: molecular dynamics with LAMMPS

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d8dc4d3-787a-4b7f-9c6c-51e4f7f86467 · outbound

This paper cites GRACE: an agentic AI for particle physics experiment design and simulation ; 2026.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language GRACE: an agentic AI for particle physics experiment design and simulation ; 2026

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5511e7fb-efc0-4a9e-8209-02e513c962db · outbound

This paper cites Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35839785-28fd-486b-9ecb-22dda7be9f28 · outbound

This paper cites DocPrompting: Generating Code by Retrieving the Docs.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language DocPrompting: Generating Code by Retrieving the Docs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed989457-4c9a-47d9-8abd-7668b2dd119f · outbound

This paper cites DocCGen: Document-based Controlled Code Generation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language DocCGen: Document-based Controlled Code Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e1b44e7-7e3e-4872-ad10-01ae6563dd02 · outbound

This paper cites MetaGPT: Meta programming for a multi-agent collabo- rative framework.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language MetaGPT: Meta programming for a multi-agent collabo- rative framework

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15c7861c-7add-4412-a054-9af9e2760ced · outbound

This paper cites AutoGen: Enabling next-gen LLM applications via multi-agent conversation.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language AutoGen: Enabling next-gen LLM applications via multi-agent conversation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f42b1bd-8b7f-4ad2-8848-b9f1feb20171 · outbound

This paper cites SciAgents: Automating scientific discovery through bioinspired multi-agent intelligent graph reasoning.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language SciAgents: Automating scientific discovery through bioinspired multi-agent intelligent graph reasoning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b28d99c9-199b-44fd-a2bd-2f5f8ad4f558 · outbound

This paper cites SWE-agent: Agent-computer interfaces enable automated software engineering.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language SWE-agent: Agent-computer interfaces enable automated software engineering

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aab0b677-b066-4aac-b79c-f88ed43ce24d · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language ReAct: Synergizing reasoning and acting in language models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77893e61-e976-4871-8ceb-b54da612f8a7 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Self-refine: Iterative refinement with self-feedback

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3650f9e5-6de9-45a2-a462-2c478eb25457 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement 20 learning.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Reflexion: Language agents with verbal reinforcement 20 learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bddc33ad-7626-4c93-b482-0c8266373cea · outbound

This paper cites Large language models cannot self-correct reasoning yet.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Large language models cannot self-correct reasoning yet

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40e6902e-b75a-44bd-ba15-268027f2cd00 · outbound

This paper cites Is self-repair a silver bullet for code generation? In: The Twelfth International Conference on Learning Representations (ICLR); 2024.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Is self-repair a silver bullet for code generation? In: The Twelfth International Conference on Learning Representations (ICLR); 2024

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bdb19ce-56ff-4bde-b79f-e1e2f2497bac · outbound

This paper cites When can LLMs actually correct their own mistakes? A critical survey of self-correction of LLMs.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language When can LLMs actually correct their own mistakes? A critical survey of self-correction of LLMs

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65e5bce6-6bc3-47e8-a30c-e4b7f8017a84 · outbound

This paper cites LiveCodeBench: Holistic and contamination free evaluation of large language models for code.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language LiveCodeBench: Holistic and contamination free evaluation of large language models for code

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf91b133-af1e-49c7-ae73-c58328577741 · outbound

This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ca96384-62a1-4cea-aa1d-2d3c332f1651 · outbound

This paper cites Codex CLI: Command-line coding agent [https://github.com/openai/codex]; 2025.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Codex CLI: Command-line coding agent [https://github.com/openai/codex]; 2025

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ffd9203-55d5-4113-bb45-fc810badda2f · outbound

This paper cites OpenAI Agents SDK [https://github.com/openai/openai-agents-python].

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language OpenAI Agents SDK [https://github.com/openai/openai-agents-python]

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 968c8a8d-0454-4d0d-855b-0ecb0dbf56a2 · outbound

This paper cites an unresolved cited work.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7f85bdd-9ed9-4a06-94d9-dbf1870a0fce · outbound

This paper cites XCOM: Photon cross section database (version 1.5) [National institute of standards and technology, gaithersburg, md]; 2010.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language XCOM: Photon cross section database (version 1.5) [National institute of standards and technology, gaithersburg, md]; 2010

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 756cc65b-d048-4e7a-b306-b23f4059fe35 · outbound

This paper cites Nuclear data sheets for A = 137.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Nuclear data sheets for A = 137

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b50c2e4a-5bef-46a4-9afc-9b8305f862ef · outbound

This paper cites Benchmark study of particle and heavy-ion trans- port code system using shielding integral benchmark archive and database for accelerator- shielding experiments.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Benchmark study of particle and heavy-ion trans- port code system using shielding integral benchmark archive and database for accelerator- shielding experiments

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6803b39b-0930-40ce-b46f-27ca02a5b544 · outbound

This paper cites Validation of the physical and RBE-weighted dose estimator based on PHITS coupled with a microdosimetric kinetic model for proton therapy.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Validation of the physical and RBE-weighted dose estimator based on PHITS coupled with a microdosimetric kinetic model for proton therapy

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66efbf9a-2390-4974-932a-05a3afcc2523 · outbound

This paper cites Improvements in the particle and heavy-ion transport code system (PHITS) for simulating neutron-response functions and detection efficiencies of a liquid organic scintillator.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Improvements in the particle and heavy-ion transport code system (PHITS) for simulating neutron-response functions and detection efficiencies of a liquid organic scintillator

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb0acfbc-db60-42de-8e41-4b4f0a01d4b6 · outbound

This paper cites A PHITS-based computational model of a TRIGA-fueled subcritical reactor for gamma dose mapping.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language A PHITS-based computational model of a TRIGA-fueled subcritical reactor for gamma dose mapping

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75b2fa6e-a836-43e6-bfc1-d3c6ebcfca5d · outbound

This paper cites Dose estimation for astronauts using dose conversion coeffi- cients calculated with the PHITS code and the ICRP/ICRU adult reference computational phantoms.

PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language Dose estimation for astronauts using dose conversion coeffi- cients calculated with the PHITS code and the ICRP/ICRU adult reference computational phantoms

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-14T15:42:46.891891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers