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Paper Citation Record · LEDGER

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space

As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2411.12010.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.12010 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:06:15.669669Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:21:08.907629Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-14T04:21:10.718275Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5953c39d-6d14-4d27-af38-ab11019ce1c2 · outbound

This paper cites Deep Learning-Based Predictions of Gene Perturbation Effects Do Not yet Outperform Simple Linear Methods.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Deep Learning-Based Predictions of Gene Perturbation Effects Do Not yet Outperform Simple Linear Methods

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 1ec29d19-d5f8-403e-8ce6-e8e15d9da9be · outbound

This paper cites Learning to Make Decisions via Submodular Regularization.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Learning to Make Decisions via Submodular Regularization

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation eb4cf77e-d307-40c3-861e-ac0f779a7652 · outbound

This paper cites Combinatorial Drug Therapy for Cancer in the Post-Genomic Era.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Combinatorial Drug Therapy for Cancer in the Post-Genomic Era

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 84609966-26c0-49c2-86c7-df7664c85745 · outbound

This paper cites Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder

Reference 4

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local_arxiv, observed 2026-08-12T18:06:15.967542Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 7aa88323-7b7b-417c-ba6f-cdc10032ff8c · outbound

This paper cites RECOVER Identifies Synergistic Drug Combinations in Vitro through Sequential Model Optimization.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space RECOVER Identifies Synergistic Drug Combinations in Vitro through Sequential Model Optimization

Reference 5

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Source-reported events for the cited work

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Observation 115687cf-9391-4114-bef7-d82b7c112346 · outbound

This paper cites On Initial Pools for Deep Active Learning.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space On Initial Pools for Deep Active Learning

Reference 6

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local_arxiv, observed 2026-08-12T18:06:15.885104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation fc979d25-5965-4e1b-b9e3-9d5ba9db6607 · outbound

This paper cites scGPT: Toward Building a Foundation Model for Single-Cell Multi-Omics Using Generative AI.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space scGPT: Toward Building a Foundation Model for Single-Cell Multi-Omics Using Generative AI

Reference 7

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f01fd405-0e86-4e66-9da9-36b197ce3163 · outbound

This paper cites Active Machine Learning Helps Drug Hunters Tackle Biology.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Active Machine Learning Helps Drug Hunters Tackle Biology

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.538140Z digest=sha256:3770d6971bef8f27c776d50565740791687913c822bc2a65f60837fe6360a0c0

Observation d2cdcf92-7164-4299-879c-2c2ab45e7b3a · outbound

This paper cites A Tutorial on Bayesian Optimization.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space A Tutorial on Bayesian Optimization

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:06:15.542411Z digest=sha256:6af10489da29926fae49cd3b5c5c9bfc8e9ea55d075fa76c8d4218d45be6bf11

Observation b41eef21-f936-4c01-a135-0859a10e6486 · outbound

This paper cites Season combinatorial intervention predictions with Salt & Peper.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Season combinatorial intervention predictions with Salt & Peper

Reference 10

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no resolver link, observed 2026-08-12T18:06:15.547000Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T18:06:15.547000Z digest=sha256:f459b0d5d9b3836cb8e1c85006e46828d3e4a16453d63cb7def6ec8c5f5d99b3

Observation 60606f92-1015-4284-878b-8d099b1a9121 · outbound

This paper cites Systematically Characterizing the Roles of E3-Ligase Family Members in Inflammatory Responses with Massively Parallel Perturb-Seq.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Systematically Characterizing the Roles of E3-Ligase Family Members in Inflammatory Responses with Massively Parallel Perturb-Seq

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 39f025f0-4317-4dc4-baa7-7680d7ad136e · outbound

This paper cites Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization

Reference 12

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Observation 1586c0ae-548b-4216-9dbf-f01e279bcecb · outbound

This paper cites Oral Nirmatrelvir for High-Risk, Nonhospitalized Adults with Covid-19.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Oral Nirmatrelvir for High-Risk, Nonhospitalized Adults with Covid-19

Reference 13

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raw_fallback, observed 2026-08-12T18:06:16.227351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 425e242e-dafa-43d0-a404-f7d68fa88d72 · outbound

This paper cites Large-Scale Foundation Model on Single-Cell Transcriptomics.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Large-Scale Foundation Model on Single-Cell Transcriptomics

Reference 14

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raw_fallback, observed 2026-08-12T18:06:16.213154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3fb99c5e-bf47-4fe3-be84-52ffa6ccf767 · outbound

This paper cites Mapping the Genetic Landscape of Human Cells.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Mapping the Genetic Landscape of Human Cells

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f68b9c5f-9123-420d-9521-7bc05da48ff4 · outbound

This paper cites an unresolved cited work.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Unresolved cited work

Reference 16

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raw_fallback, observed 2026-08-12T18:06:16.184916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cd093ca7-81ef-479e-b4fd-caec3fba74a5 · outbound

This paper cites Additivity Predicts the Efficacy of Most Approved Combination Therapies for Advanced Cancer.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Additivity Predicts the Efficacy of Most Approved Combination Therapies for Advanced Cancer

Reference 17

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0795d684-49ee-4fed-9c50-1c590c3a67bf · outbound

This paper cites Triple–Hormone-Receptor Agonist Retatrutide for Obesity — A Phase 2 Trial.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Triple–Hormone-Receptor Agonist Retatrutide for Obesity — A Phase 2 Trial

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6a20638d-09c1-47a4-b629-7f1151757756 · outbound

This paper cites Auto-Encoding Variational Bayes.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Auto-Encoding Variational Bayes

Reference 19

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Source-reported events for the cited work

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Observation 1b7c3a0a-7107-44da-856a-38f570244140 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Semi-Supervised Classification with Graph Convolutional Networks

Reference 20

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Observation 70af035a-9fcd-47de-810c-f7652ad47f10 · outbound

This paper cites DEUP: Direct Epistemic Uncertainty Prediction.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space DEUP: Direct Epistemic Uncertainty Prediction

Reference 21

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Observation 44ef0fc4-3622-4606-86d7-caab522dd199 · outbound

This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Reference 22

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source=pdf_text observed=2026-08-12T18:06:15.606241Z digest=sha256:7cdeeabaa847f2abab0cc859b0b7b8ecd5773e6a4fec5fe0cbe64dafc2cb0c9e

Observation e64c313d-42ed-4e66-8246-4a69bfff1bd3 · outbound

This paper cites Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling

Reference 23

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 24900d03-86ab-4cc4-b9dc-ab772a73ee2d · outbound

This paper cites Predicting Cellular Responses to Complex Perturbations in High- throughput Screens.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Predicting Cellular Responses to Complex Perturbations in High- throughput Screens

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a326fbc2-c291-4bbc-91f7-8198ebe246b9 · outbound

This paper cites Combination Therapy in Combating Cancer.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Combination Therapy in Combating Cancer

Reference 25

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verified fuzzy
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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6c78f986-a4b5-4fae-ad4d-0d0626e35774 · outbound

This paper cites Exploring Genetic Interaction Manifolds Constructed from Rich Single-Cell Phenotypes.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Exploring Genetic Interaction Manifolds Constructed from Rich Single-Cell Phenotypes

Reference 26

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raw_fallback, observed 2026-08-12T18:06:16.114411Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6203291b-7f5e-4dec-81d1-8e8675484b8a · outbound

This paper cites Rationalizing Combination Therapies.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Rationalizing Combination Therapies

Reference 27

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raw_fallback, observed 2026-08-12T18:06:16.099698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.629175Z digest=sha256:6847236e7b84a4e915e3f687cc4da81bece04b539e08c619501f0cc7fa2fd48a

Observation 8632047e-8050-420d-af34-b99e526fdb91 · outbound

This paper cites Toward a Foundation Model of Causal Cell and Tissue Biology with a Perturbation Cell and Tissue Atlas.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Toward a Foundation Model of Causal Cell and Tissue Biology with a Perturbation Cell and Tissue Atlas

Reference 28

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raw_fallback, observed 2026-08-12T18:06:16.085615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ca676afd-eb8f-4a5d-843f-b97803f2b73e · outbound

This paper cites Predicting Transcriptional Outcomes of Novel Multigene Perturbations with GEARS.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Predicting Transcriptional Outcomes of Novel Multigene Perturbations with GEARS

Reference 29

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raw_fallback, observed 2026-08-12T18:06:16.071399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e25f384f-f35b-416e-bf6a-7a6bd7c91a1a · outbound

This paper cites How May GIP Enhance the Therapeutic Efficacy of GLP-1?.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space How May GIP Enhance the Therapeutic Efficacy of GLP-1?

Reference 30

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raw_fallback, observed 2026-08-12T18:06:16.057380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation db0e24a6-9565-4e13-b632-0125a24218db · outbound

This paper cites Drug Combination Therapy for Emerging Viral Diseases.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Drug Combination Therapy for Emerging Viral Diseases

Reference 31

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raw_fallback, observed 2026-08-12T18:06:16.042171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.647046Z digest=sha256:0e09a4b63b3ac021ef924e7c14392a7a38ee139a7fc5a59fa58527bba0c7258b

Observation 85c43600-85af-4f12-9888-b76628dee98c · outbound

This paper cites Mapping the Genetic Interaction Network of PARP Inhibitor Response.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Mapping the Genetic Interaction Network of PARP Inhibitor Response

Reference 32

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verified exact
doi, observed 2026-08-12T18:06:15.706041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.651394Z digest=sha256:0fb51a3b35681f90fc7b60abe4995d552395f4a1a8fbd5ae9af7a3dc786d7646

Observation 89e58d02-1013-41d3-8b12-1068908cf041 · outbound

This paper cites Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures by Defined Factors.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures by Defined Factors

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-12T18:06:16.027296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.655904Z digest=sha256:a364ac59539c8035207ace6edbf162da50f1cdf648a9da9aadf5757729c11b4f

Observation b2cafa5c-bc21-4fb4-b869-e24245e30499 · outbound

This paper cites A Versatile CRISPR-Cas13d Platform for Multiplexed Transcriptomic Regulation and Metabolic Engineering in Primary Human T Cells.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space A Versatile CRISPR-Cas13d Platform for Multiplexed Transcriptomic Regulation and Metabolic Engineering in Primary Human T Cells

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-12T18:06:16.012404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.660163Z digest=sha256:c527b555b550ff89af72ef02a9cf0260d52e627c55607fe18728330dcb69b829

Observation c1c7dc98-c7f2-4100-ac3e-c722c5457887 · outbound

This paper cites Submodularity in Data Subset Selection and Active Learning.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Submodularity in Data Subset Selection and Active Learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:06:15.997152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.664544Z digest=sha256:2c1cfe3cd9c9784064cd727f38e96188ebc80ec9dd347cd28ffdc85c6458482d

Observation ec6e577a-9843-4bda-8a3f-d7fcba5f918d · outbound

This paper cites an unresolved cited work.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Unresolved cited work

Reference 1024

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T18:06:15.982808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.669669Z digest=sha256:6d3861af9ea67d67f1157fc4354b19c9cb91442f4a97308fa41acb6e277f9211

Observation 1763ff18-2a29-4052-ae49-476273d8071f · outbound

This paper cites Engineered CRISPR-Cas12a for Higher-Order Combinatorial Chromatin Perturbations.

Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space Engineered CRISPR-Cas12a for Higher-Order Combinatorial Chromatin Perturbations

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:06:16.170969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T18:06:15.578670Z digest=sha256:65e353f3cac1b8e0671a04b354ed4550983025a724ce657e5ee996f3101ff8fe

Pith citing papers

Observation 1cfb0672-bd08-4d37-a315-fee992df51f2 · inbound

Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models cites this paper.

Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models Active learning for efficient discovery of optimal gene combinations in the combinatorial perturbation space

Reference 48

Resolution
metadata mismatch
local_arxiv, observed 2026-08-14T04:21:10.724986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-14T04:21:08.907629Z digest=sha256:c5462031322e376c8efe8fc60355fd6a23c524adc5bf51e4b839fcd470f3a135