A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML | Paper Citation Record

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This paper cites Molecular representations in AI -driven drug discovery: a review and practical guide.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Molecular representations in AI -driven drug discovery: a review and practical guide

Reference 1

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This paper cites P.; Kulik, H.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML P.; Kulik, H

Reference 2

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 3

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This paper cites Internally Consistent Prediction of Vapor Pressure and Related Properties.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Internally Consistent Prediction of Vapor Pressure and Related Properties

Reference 4

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 5

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This paper cites J.; Holder, G.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML J.; Holder, G

Reference 6

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This paper cites Prediction of Fluid Phase Behavior from Molecular Models.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Prediction of Fluid Phase Behavior from Molecular Models

Reference 7

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This paper cites S.; Hilal, S.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML S.; Hilal, S

Reference 8

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 9

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Observation 15f66974-c6f5-4624-814a-131ba41f0258 · outbound

This paper cites W.; Craighead, J.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML W.; Craighead, J

Reference 10

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This paper cites Trends in clinical success rates and therapeutic focus.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Trends in clinical success rates and therapeutic focus

Reference 11

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Observation 8617d3cd-4413-46b8-9876-24738b225fd5 · outbound

This paper cites Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

Reference 12

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 13

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This paper cites N.; Remijan, A.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML N.; Remijan, A

Reference 14

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 15

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 16

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This paper cites XGBoost : A Scalable Tree Boosting System.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML XGBoost : A Scalable Tree Boosting System

Reference 17

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This paper cites LightGBM : A Highly Efficient Gradient Boosting Decision Tree.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML LightGBM : A Highly Efficient Gradient Boosting Decision Tree

Reference 18

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This paper cites V.; Gulin, A.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML V.; Gulin, A

Reference 19

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 20

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This paper cites an unresolved cited work.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 21

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Observation d5732ee7-49e6-4715-a239-d46e65bebe6a · outbound

This paper cites SMILES , a chemical language and information system.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML SMILES , a chemical language and information system

Reference 22

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 23

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This paper cites Self-referencing embedded strings ( SELFIES ): A 100\.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Self-referencing embedded strings ( SELFIES ): A 100\

Reference 24

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 25

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 26

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This paper cites 2019; https://www.python.org/, Version 3.12.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML 2019; https://www.python.org/, Version 3.12

Reference 27

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 28

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 29

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This paper cites Optuna: A Next-generation Hyperparameter Optimization Framework.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Optuna: A Next-generation Hyperparameter Optimization Framework

Reference 30

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This paper cites Dask: Parallel Computation with Blocked algorithms and Task Scheduling.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Dask: Parallel Computation with Blocked algorithms and Task Scheduling

Reference 31

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Observation d6cfbdb5-1658-4d0f-b24d-eac5cf2d3b46 · outbound

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML R., Brunno, T

Reference 32

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This paper cites A.; Cheng, T.; Zhang, J.; Gindulyte, A.; Bolton, E.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML A.; Cheng, T.; Zhang, J.; Gindulyte, A.; Bolton, E

Reference 33

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This paper cites https://github.com/mcs07/CIRpy.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML https://github.com/mcs07/CIRpy

Reference 34

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This paper cites 2024; https://github.com/cleanlab/cleanlab, original-date: 2018-05-11T01:55:21Z.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML 2024; https://github.com/cleanlab/cleanlab, original-date: 2018-05-11T01:55:21Z

Reference 35

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Observation ec2d8438-d49b-4229-b5fc-6df17e3ae1ea · outbound

This paper cites Detecting Errors in Numerical Data via any Regression Model.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Detecting Errors in Numerical Data via any Regression Model

Reference 36

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This paper cites Model-agnostic label quality scoring to detect real-world label errors.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Model-agnostic label quality scoring to detect real-world label errors

Reference 37

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 38

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Observation 02f44f01-2c30-4da3-b32c-c47eb2ddb183 · outbound

This paper cites M.; Sayle, R.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML M.; Sayle, R

Reference 39

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 40

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Observation 3ffe4113-219e-47bc-acb4-fe060074a27a · outbound

This paper cites DeepTox : Toxicity Prediction using Deep Learning.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML DeepTox : Toxicity Prediction using Deep Learning

Reference 41

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Observation 66a40893-5567-49ac-b9b6-59f4e6b4a880 · outbound

This paper cites Profiling Prediction of Kinase Inhibitors : Toward the Virtual Assay.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Profiling Prediction of Kinase Inhibitors : Toward the Virtual Assay

Reference 42

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Observation bde52320-12ff-48f0-8dff-fb13347c4878 · outbound

This paper cites A.; Fulle, S.; Merget, B.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML A.; Fulle, S.; Merget, B

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.892343Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 42857269-0746-4e4d-9151-f172f2a296a4 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Efficient Estimation of Word Representations in Vector Space

Reference 44

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Observation ba78a6b0-bf8a-433d-b9e6-134153bdf717 · outbound

This paper cites Extended- Connectivity Fingerprints.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Extended- Connectivity Fingerprints

Reference 45

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Observation 8e7408c4-1958-48f8-b734-490b34ba1e25 · outbound

This paper cites Repurposed drugs and nutraceuticals targeting envelope protein: A possible therapeutic strategy against COVID -19.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Repurposed drugs and nutraceuticals targeting envelope protein: A possible therapeutic strategy against COVID -19

Reference 46

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Observation 5e1df902-3e0f-4cc0-82a4-c07299ad4b36 · outbound

This paper cites Identifying Structure – Property Relationships through SMILES Syntax Analysis with Self - Attention Mechanism.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Identifying Structure – Property Relationships through SMILES Syntax Analysis with Self - Attention Mechanism

Reference 47

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Observation d85ea893-7357-4460-83e9-5e4478f794a9 · outbound

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A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 48

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Observation cc770606-49f3-478e-9be4-8f92384036e5 · outbound

This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 49

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This paper cites Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.813544Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 898107eb-143c-4d52-8e35-ed572455b39e · outbound

This paper cites Analyzing Learned Molecular Representations for Property Prediction.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Analyzing Learned Molecular Representations for Property Prediction

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.795927Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fa049f84-3d6a-47f7-bf4a-efcdb2e4033d · outbound

This paper cites Correction to Analyzing Learned Molecular Representations for Property Prediction.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Correction to Analyzing Learned Molecular Representations for Property Prediction

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.782580Z

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Observation d3c1b0c5-9e4f-4d34-bc60-c91547def168 · outbound

This paper cites SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties

Reference 53

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Observation 1a8f236a-49ba-4620-ab45-bfc1c7d68809 · outbound

This paper cites ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 54

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Observation f569bd0a-6108-41cf-a29f-c6c86d20816a · outbound

This paper cites Mol- BERT : An Effective Molecular Representation with BERT for Molecular Property Prediction.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Mol- BERT : An Effective Molecular Representation with BERT for Molecular Property Prediction

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.769550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7fdcdd73-1899-4e06-8312-1d11a87e10f3 · outbound

This paper cites Large-Scale Chemical Language Representations Capture Molecular Structure and Properties.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Large-Scale Chemical Language Representations Capture Molecular Structure and Properties

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:56.208819Z

Source-reported events for the cited work

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Observation 47903eda-6e89-46dd-8833-b9fe6b0500c7 · outbound

This paper cites G.; Jung, G.; Cole, J.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML G.; Jung, G.; Cole, J

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.751453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 468104f5-d8aa-40ac-a2fe-fae11bde83ac · outbound

This paper cites G.; Jung, G.; Cole, J.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML G.; Jung, G.; Cole, J

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.736151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2df66df-635f-459b-8557-7b18ae89cb5a · outbound

This paper cites Functionality pattern matching as an efficient complementary structure/reaction search tool: an open-source approach.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Functionality pattern matching as an efficient complementary structure/reaction search tool: an open-source approach

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.720592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b569e8ed-3e62-4ba3-b944-8ce220b14442 · outbound

This paper cites A Density - Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML A Density - Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.704404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b145e347-16dc-4e9f-bd05-f8418db7d31a · outbound

This paper cites P.; Xu, X.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML P.; Xu, X

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.686879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 58b8f6c4-fdd7-424b-9551-d18cbfeee1ec · outbound

This paper cites Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:56.233229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcfdb427-ecf5-4a14-a54b-2f2732bfd85d · outbound

This paper cites Practical Bayesian Optimization of Machine Learning Algorithms.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Practical Bayesian Optimization of Machine Learning Algorithms

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:56.236815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0e093d3-a72d-4476-a08c-b13749b7f8fc · outbound

This paper cites an unresolved cited work.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:54:56.656078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0e61f9e5-f1f3-4e72-ab00-c333a203e9e2 · outbound

This paper cites V.; Sushko, Y.; Novotarskyi, S.; Patiny, L.; Kondratov, I.; Petrenko, A.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML V.; Sushko, Y.; Novotarskyi, S.; Patiny, L.; Kondratov, I.; Petrenko, A

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:54:56.641311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 96ebb7c6-857b-4f57-bf44-36f31d1ab60a · outbound

This paper cites sWE䮨 &HHܳȌ犈? _o_|? G|W |W CK ׃/__ ۿm w s<S] ǥw k 5 ;s Ꮖ ]5y?=n hH ; ) =ۿHGG;)+BL=;4A|O &>.

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML sWE䮨 &HHܳȌ犈? _o_|? G|W |W CK ׃/__ ۿm w s<S] ǥw k 5 ;s Ꮖ ]5y?=n hH ; ) =ۿHGG;)+BL=;4A|O &>

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T21:54:56.246937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

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