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Paper Citation Record · LEDGER

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction

As of 10 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2506.18797.

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

pith.paper-citation-record.v1
2506.18797 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:19:29.242145Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:53:29.775425Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:53:36.353986Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 05d9ed89-748a-4726-8d91-f7f98652c2b5 · outbound

This paper cites Chapter 12: Human microbiome analysis.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Chapter 12: Human microbiome analysis

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7c3a77e4-ea73-4977-88a2-d89e950e048f · outbound

This paper cites The healthy human microbiome.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction The healthy human microbiome

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1104fdac-1548-4a23-b2d5-8704e5357f6d · outbound

This paper cites Mapping human microbiome drug metabolism by gut bacteria and their genes.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Mapping human microbiome drug metabolism by gut bacteria and their genes

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e38e8238-7072-47fd-a566-e6c442a96392 · outbound

This paper cites What are the consequences of the disappearing human microbiota? Nature Reviews Microbiology, 7(12):887–894, 2009.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction What are the consequences of the disappearing human microbiota? Nature Reviews Microbiology, 7(12):887–894, 2009

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:26.604852Z digest=sha256:dc8b28ba93bfd8bf839cca7b4efec31fd0783b14500fbfde600e5a5bb5b41c65

Observation a2b1a3c8-4046-43de-8dfa-a3dbffcdc25a · outbound

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

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Semi-Supervised Classification with Graph Convolutional Networks

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:19:26.736585Z digest=sha256:3104eb8b616f7bd1d4387d43b0752ffc26c2e5cad962313b255c4376fc46545e

Observation f8a1a259-600b-4140-b981-8591a6e777f2 · outbound

This paper cites Predicting human microbe–drug associ- ations via graph convolutional network with conditional random field.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Predicting human microbe–drug associ- ations via graph convolutional network with conditional random field

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation eff9c882-4cde-481f-af6b-881febba66ec · outbound

This paper cites Gnaemda: microbe-drug associations prediction on graph normalized convolutional network.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Gnaemda: microbe-drug associations prediction on graph normalized convolutional network

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b452f3f3-ba5d-4c3a-afc8-ec8d86eb7811 · outbound

This paper cites Microbe-disease association prediction using rgcn through microbe-drug- disease network.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Microbe-disease association prediction using rgcn through microbe-drug- disease network

Reference 8

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raw_fallback, observed 2026-08-06T23:19:34.343646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7bdea81a-84e9-487d-9c0c-9762d119bc41 · outbound

This paper cites Graph attention networks.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Graph attention networks

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation caf3d08b-d981-474e-af46-33c67e5344aa · outbound

This paper cites Ensembling graph attention networks for human microbe–drug association predic- tion.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Ensembling graph attention networks for human microbe–drug association predic- tion

Reference 10

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raw_fallback, observed 2026-08-06T23:19:33.830866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b5d4da89-a23a-4e56-8ade-3912bed2f864 · outbound

This paper cites Mgatmda: Predicting microbe-disease associations via multi-component graph attention network.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Mgatmda: Predicting microbe-disease associations via multi-component graph attention network

Reference 11

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raw_fallback, observed 2026-08-06T23:19:33.618358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0230a266-f2e8-4b6f-90f3-41b78a7f2668 · outbound

This paper cites Heterogeneous graph attention network.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Heterogeneous graph attention network

Reference 12

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raw_fallback, observed 2026-08-06T23:19:33.396846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e2c170b8-4ba1-4af4-9a67-b6477c0c3a69 · outbound

This paper cites Mdmd: a computational model for predicting drug- related microbes based on the aggregated metapaths from a heterogeneous network.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Mdmd: a computational model for predicting drug- related microbes based on the aggregated metapaths from a heterogeneous network

Reference 13

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raw_fallback, observed 2026-08-06T23:19:33.158697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:27.554177Z digest=sha256:f76e336788be4669dc9ca078cd12d83de7635a57aa45f94d5132871d11844e89

Observation 84b1dad3-fa7a-446f-9301-7f62e9b923f0 · outbound

This paper cites Multi-scale topology and position feature learning and relationship- aware graph reasoning for prediction of drug-related microbes.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Multi-scale topology and position feature learning and relationship- aware graph reasoning for prediction of drug-related microbes

Reference 14

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raw_fallback, observed 2026-08-06T23:19:32.888549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:27.657881Z digest=sha256:e17b0bddd96639516c511a86796fe043e0d78a9fdd4f3ea4a8fa423f8a6de5db

Observation c76c9c64-74d3-486a-b681-2613939183a1 · outbound

This paper cites Dynamic category- sensitive hypergraph inferring and homo-heterogeneous neighbor feature learning for drug-related microbe pre- JOURNAL OF LATEX CLASS FILES, VOL.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Dynamic category- sensitive hypergraph inferring and homo-heterogeneous neighbor feature learning for drug-related microbe pre- JOURNAL OF LATEX CLASS FILES, VOL

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c2aecd90-a7f6-4302-8bb8-071750dc16cd · outbound

This paper cites Mkgcn: multi-modal knowledge graph convolutional network for music recommender systems.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Mkgcn: multi-modal knowledge graph convolutional network for music recommender systems

Reference 16

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raw_fallback, observed 2026-08-06T23:19:32.451242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:27.864117Z digest=sha256:64ca2d0955b7417f51e2b9f5201305df9dd986a4a7445f7d213ec9516cbadca0

Observation ca5e6cd4-2edf-4658-9933-8423be44cd89 · outbound

This paper cites Gacnnmda: a com- putational model for predicting potential human microbe- drug associations based on graph attention network and cnn-based classifier.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Gacnnmda: a com- putational model for predicting potential human microbe- drug associations based on graph attention network and cnn-based classifier

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 93691fd6-8161-46f8-a6c5-75f473efdcdf · outbound

This paper cites Predicting of microbe-drug asso- ciations via a pre-completion-based label propagation algorithm.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Predicting of microbe-drug asso- ciations via a pre-completion-based label propagation algorithm

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 789cfbd6-bd98-43f6-874a-5ad30bd6b03d · outbound

This paper cites A data-driven approach for predicting the impact of drugs on the human microbiome.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction A data-driven approach for predicting the impact of drugs on the human microbiome

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T23:19:31.766316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.204466Z digest=sha256:a0f4650b11de6fe565d3224cb0d4a18ab930d6daefa598baa5da0c01fd026f4a

Observation 17210654-9ee4-427f-9d0c-e135d800856e · outbound

This paper cites Prediction of microbe-drug associations based on katz measure.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Prediction of microbe-drug associations based on katz measure

Reference 20

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raw_fallback, observed 2026-08-06T23:19:31.535072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.327181Z digest=sha256:c771c43f4409253b39a9fdd8e9150c9864684d02d9ce66ff4b615a74aead2542

Observation 936fcf8e-af73-46e2-b0fa-31734f8513a1 · outbound

This paper cites Association mining to iden- tify microbe drug interactions based on heterogeneous network embedding representation.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Association mining to iden- tify microbe drug interactions based on heterogeneous network embedding representation

Reference 21

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raw_fallback, observed 2026-08-06T23:19:31.345777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.433750Z digest=sha256:23c73bd2b3294e58213d11ac87a60ce089074fcc6f7188abac39cbc39c5d323c

Observation a2e20bb5-3e8f-4e0b-9e2e-ea216638fdbf · outbound

This paper cites Predicting microbe-drug association based on similarity and semi-supervised learning.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Predicting microbe-drug association based on similarity and semi-supervised learning

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-06T23:19:31.095420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 090d3e54-e36e-48e5-bf6e-9e2b4c2bae7a · outbound

This paper cites Gsamda: a com- putational model for predicting potential microbe–drug associations based on graph attention network and sparse autoencoder.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Gsamda: a com- putational model for predicting potential microbe–drug associations based on graph attention network and sparse autoencoder

Reference 23

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raw_fallback, observed 2026-08-06T23:19:30.822145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.624220Z digest=sha256:e4b6cd123ba8cc2381d9518d03137cba8de7fa6cac86989f85b9e9861fe94627

Observation 8a8a6088-5fdf-4f26-ab6a-d2bb261aca99 · outbound

This paper cites A survey on information bottleneck.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction A survey on information bottleneck

Reference 24

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raw_fallback, observed 2026-08-06T23:19:30.618781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.727972Z digest=sha256:8d60025eff808876458541aa99b36317f3c6c5ccd14e21b7718f68bdcb20f853

Observation f4b96739-a952-4f1e-b504-46b9cd962546 · outbound

This paper cites Mdad: a special resource for microbe-drug associations.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Mdad: a special resource for microbe-drug associations

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T23:19:30.382127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.818719Z digest=sha256:086d04d9722d31764b0165348204125ff0d588bc827b13a52eae6d09e720f327

Observation 8bdcb2fa-1351-411e-a8d8-19744ef93e20 · outbound

This paper cites Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy

Reference 26

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raw_fallback, observed 2026-08-06T23:19:30.157642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:28.947343Z digest=sha256:b933f1f73fe249ead86616d727777750de8272b6b859cd2fcca89bc3e14ee0a9

Observation d2285683-d257-4f71-8b3c-b0470d77ab5d · outbound

This paper cites Multimodal evaluation of drug antibacterial activity reveals cinnamaldehyde analog anti-biofilm ef- fects against haemophilus influenzae.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Multimodal evaluation of drug antibacterial activity reveals cinnamaldehyde analog anti-biofilm ef- fects against haemophilus influenzae

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T23:19:29.938639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:29.043597Z digest=sha256:96a46780e3c8bff7f72da7252e3dfa80cc588788107dbee6d3dc13a8288ede68

Observation 3ec0b15f-078e-4e3a-a967-e50d2b9f2259 · outbound

This paper cites The vibrio cholerae type vi secretion system: toxins, regulators and consequences.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction The vibrio cholerae type vi secretion system: toxins, regulators and consequences

Reference 28

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raw_fallback, observed 2026-08-06T23:19:29.745708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:29.160877Z digest=sha256:f1023970968ea87b7f370412e7ad100158e78f66a06d8ea4815fd6f65b68764a

Observation 45f94ff9-60af-4aaa-88b4-edc37bad58dc · outbound

This paper cites an unresolved cited work.

A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction Unresolved cited work

Reference 29

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unresolved
raw_fallback, observed 2026-08-06T23:19:29.536423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T23:19:29.242145Z digest=sha256:bac1136e37476b960703aad79e179ad1c5799cd5cc724bf929a83a6ce7489183

Pith citing papers

Observation b47a400e-41df-4d78-b66f-418851a031fa · inbound

SOC-DGL: Social Interaction Behavior Inspired Dual Graph Learning Framework for Drug-Target Interaction Identification cites this paper.

SOC-DGL: Social Interaction Behavior Inspired Dual Graph Learning Framework for Drug-Target Interaction Identification A Multi-view Divergence-Convergence Feature Augmentation Framework for Drug-related Microbes Prediction

Reference 3

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verified exact
local_arxiv, observed 2026-08-07T11:53:36.416888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:53:29.775425Z digest=sha256:8a6ddb98e0cc7838b113ebece6ad711cac9566ab3d59d976a672967ea75ec169