Paper Citation Record · LEDGER

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2411.18442.

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

pith.paper-citation-record.v1
2411.18442 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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Pith citing papers itemized under the disclosed page cap.

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

Source: pith, observed 2026-08-12T11:16:46.873972Z

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation 8bcb795e-d4c5-425b-9cb1-d0aef10747e2 · outbound

This paper cites Correcting sample selection bias for image classifica- tion.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Correcting sample selection bias for image classifica- tion

Reference 1

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Observation 2a4626c4-3247-4099-bfce-f64666f8c727 · outbound

This paper cites Active and Semisupervised Learning for the Classification of Remote Sensing Images.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Active and Semisupervised Learning for the Classification of Remote Sensing Images

Reference 2

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Observation 4303afbc-54ca-46c6-a2d9-90f2393d1afc · outbound

This paper cites Active learning to overcome sample selection bias: application to photometric variable star classification.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Active learning to overcome sample selection bias: application to photometric variable star classification

Reference 3

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Observation 30cd4070-4f6c-4c45-bc71-0d42405ffcde · outbound

This paper cites Reject inference in credit scoring using a three-way decision and safe semi-supervised support vector machine.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Reject inference in credit scoring using a three-way decision and safe semi-supervised support vector machine

Reference 4

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Observation 8c52a82b-308a-4201-a4d5-287b5c328d12 · outbound

This paper cites Impact of Query Sample Selection Bias on Information Retrieval System Rank- ing.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Impact of Query Sample Selection Bias on Information Retrieval System Rank- ing

Reference 5

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Observation ff675b22-5071-4911-95f1-dad9726fddc6 · outbound

This paper cites Domain Adaptation with Structural Correspondence Learning.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Domain Adaptation with Structural Correspondence Learning

Reference 6

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Observation 65727788-1729-4564-b96d-59bae0f68b2c · outbound

This paper cites Unsupervised Visual Domain Adaptation Using Subspace Alignment.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Unsupervised Visual Domain Adaptation Using Subspace Alignment

Reference 7

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Observation 8b536fc9-3878-4309-bf6c-81a4422f85e7 · outbound

This paper cites Feature-Level Domain Adaptation.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Feature-Level Domain Adaptation

Reference 8

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Observation 7773122d-17f6-404f-9f61-28b1a1a21f9a · outbound

This paper cites Learning and Evaluating Classifiers under Sample Selection Bias.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Learning and Evaluating Classifiers under Sample Selection Bias

Reference 9

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Observation 888db5e6-0939-444d-9a85-54e6be62f625 · outbound

This paper cites Decision Support and Profit Prediction for Online Auction Sell- ers.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Decision Support and Profit Prediction for Online Auction Sell- ers

Reference 10

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Observation 143d0a9f-1a25-4551-a407-d19736683bf1 · outbound

This paper cites Healing Sample Selection Bias by Source Classifier Selection.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Healing Sample Selection Bias by Source Classifier Selection

Reference 11

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Observation 83f48f2c-0adf-4935-ad6b-7f0ff79735c1 · outbound

This paper cites Learning under nonstationarity: covari- ate shift and class-balance change.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Learning under nonstationarity: covari- ate shift and class-balance change

Reference 12

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Observation a61a32d9-7a7c-4934-8c1b-63640511f0a3 · outbound

This paper cites Continuous Target Shift Adaptation in Su- pervised Learning.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Continuous Target Shift Adaptation in Su- pervised Learning

Reference 13

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Observation 7ae4f312-c5cc-4d40-a057-b073fd3270d2 · outbound

This paper cites Correcting Sample Selection Bias by Unlabeled Data.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Correcting Sample Selection Bias by Unlabeled Data

Reference 14

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Observation cd4e7603-6e1d-496f-bd82-66f84b3d5a02 · outbound

This paper cites Fair and Robust Classification Under Sample Selection Bias.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Fair and Robust Classification Under Sample Selection Bias

Reference 15

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Observation c379f14d-e774-451d-b6d0-3394a1a36adf · outbound

This paper cites Robust classification under sample selection bias.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Robust classification under sample selection bias

Reference 16

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Observation 35124912-f917-4067-b941-9e0e98a641e5 · outbound

This paper cites Robust domain-adaptive discriminant analysis.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Robust domain-adaptive discriminant analysis

Reference 17

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Observation 6f142a3e-b88b-445d-8c19-3850f6534dbd · outbound

This paper cites A survey on semi-supervised learning.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning A survey on semi-supervised learning

Reference 18

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Observation b2e4de73-d41c-4ba2-aa28-53095760c875 · outbound

This paper cites Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks

Reference 19

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Observation db5ae833-12c0-4c78-86ca-b05835c58b2a · outbound

This paper cites Radhakrishnan, J.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Radhakrishnan, J

Reference 20

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Observation 2ea8c7c1-15fb-41fb-b10b-ed47c0522d38 · outbound

This paper cites DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer Learning.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer Learning

Reference 21

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Observation 643f1e59-9e7a-4a81-a207-78be3c9b8a9b · outbound

This paper cites Arazo, D.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Arazo, D

Reference 22

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Observation cb09d113-d9c6-4d76-a745-23b8ffda0167 · outbound

This paper cites Learning a similarity metric discriminatively, with application to face verification.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Learning a similarity metric discriminatively, with application to face verification

Reference 23

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Observation b6bd67c1-91d5-448f-ac46-4e460146959a · outbound

This paper cites Scikit-learn: Machine Learning in Python.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Scikit-learn: Machine Learning in Python

Reference 24

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Observation c59cdab2-0858-4b36-bf93-0cf3736bbde9 · outbound

This paper cites Dheeru and E.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Dheeru and E

Reference 25

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Observation f340bccb-75bf-400b-8c0a-96281faf9746 · outbound

This paper cites Classification of Pistachio Species Using Im- proved K-NN Classifier.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Classification of Pistachio Species Using Im- proved K-NN Classifier

Reference 26

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Observation 73af1a2a-2399-472e-8850-f3e5c7b5c89b · outbound

This paper cites Determining the Extinguishing Status of Fuel Flames With Sound Wave by Machine Learning Methods.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Determining the Extinguishing Status of Fuel Flames With Sound Wave by Machine Learning Methods

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:47.010237Z

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Observation 424eba94-0fe3-4561-9373-bac5f9e0098a · outbound

This paper cites The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.).

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.)

Reference 28

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Observation 1026257f-d088-4da1-8984-82b827d211c5 · outbound

This paper cites Inhibition of Poly(ADP-Ribose) Polymerase in Tumors from BRCA Mutation Carriers.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Inhibition of Poly(ADP-Ribose) Polymerase in Tumors from BRCA Mutation Carriers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.993633Z

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Observation 02d1bf56-6740-4d61-bb5d-2cb12357690a · outbound

This paper cites PARP inhibitor olaparib is safe and effective in patients with BRCA1 and BRCA2 mutations.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning PARP inhibitor olaparib is safe and effective in patients with BRCA1 and BRCA2 mutations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.985033Z

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Observation 2654728d-a807-479a-9a20-429e0d2d99a2 · outbound

This paper cites Harnessing synthetic lethal interactions in anticancer drug discovery.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Harnessing synthetic lethal interactions in anticancer drug discovery

Reference 31

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Observation d55a01bf-adba-416c-a0ac-8393549cecf1 · outbound

This paper cites Overcoming selection bias in synthetic lethality prediction.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Overcoming selection bias in synthetic lethality prediction

Reference 32

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Observation aadefa98-b4fc-4766-bc35-a93a36f72cc3 · outbound

This paper cites Non-specific chemical in- hibition of the Fanconi anemia pathway sensitizes cancer cells to cisplatin.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Non-specific chemical in- hibition of the Fanconi anemia pathway sensitizes cancer cells to cisplatin

Reference 33

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Observation 3c86cdb6-5bcd-4e74-9d78-8abf4546e2bf · outbound

This paper cites Genome-wide CRISPR-Cas9 Screens Reveal Loss of Re- dundancy between PKMYT1 and WEE1 in Glioblastoma Stem-like Cells.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Genome-wide CRISPR-Cas9 Screens Reveal Loss of Re- dundancy between PKMYT1 and WEE1 in Glioblastoma Stem-like Cells

Reference 34

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Observation 4fea1924-b02d-4692-b7f2-1143f4ef6c81 · outbound

This paper cites Synthetic lethality between CCNE1 ampli- fication and loss of BRCA1.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Synthetic lethality between CCNE1 ampli- fication and loss of BRCA1

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.943762Z

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Observation 4b16a6de-a42c-43a4-b0d5-64889f4d646d · outbound

This paper cites Genome-wide RNAi screens in human brain tumor isolates reveal a novel viability requirement for PHF5A.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Genome-wide RNAi screens in human brain tumor isolates reveal a novel viability requirement for PHF5A

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.934981Z

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Observation df094f87-6c88-4b5e-a1ae-5ab1527d751b · outbound

This paper cites A synthetic lethal screen identifies FAT1 as an antagonist of caspase-8 in extrinsic apoptosis.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning A synthetic lethal screen identifies FAT1 as an antagonist of caspase-8 in extrinsic apoptosis

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.925822Z

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Observation 56c2b730-8c2d-4b59-ace1-095cb28fa322 · outbound

This paper cites ELISL: early–late integrated synthetic lethality prediction in cancer.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning ELISL: early–late integrated synthetic lethality prediction in cancer

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.917208Z

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Observation ff9ece67-da51-4cf8-91c3-658207c60bcb · outbound

This paper cites Harnessing synthetic lethality to predict the response to cancer treatment.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Harnessing synthetic lethality to predict the response to cancer treatment

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.908930Z

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Observation ab6b15d4-c8b4-41b5-ad27-257236fc77c7 · outbound

This paper cites DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:16:46.900446Z

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Observation ba30ce63-0670-491d-9193-bb7750eb0c90 · outbound

This paper cites Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning.

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning

Reference 41

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Source-reported events for the cited work

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Pith citing papers

Observation ba30ce63-0670-491d-9193-bb7750eb0c90 · inbound