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Paper Citation Record · LEDGER

On leveraging constrained smooth additive regression models for global optimization

As of 12 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2510.14122.

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

pith.paper-citation-record.v1
2510.14122 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:41:13.908471Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:35:19.588529Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4fcb4817-9205-439a-8daf-8b44b5b08ca8 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-04T09:41:11.248063Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:41:11.248063Z digest=sha256:250ab6fad0757c8a19fba87b9cf3a7404d324b81e5092abb514dbc539e969a9a

Observation 6356517a-fdd0-49d4-bb55-e77bead28431 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-04T09:41:11.289326Z digest=sha256:64edc10c9c73c6e6839ae79a431a9aa30f72c5309fae322b91b464bce6b9b3b3

Observation 42866973-e202-4ffb-9f5a-46b3f3486102 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 3

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source=pdf_text observed=2026-08-04T09:41:11.393134Z digest=sha256:05cb86a792510861df9ee4440898e277c2b1b7d30cd31666ebd6f911c4849cbb

Observation 366e7cb4-aacd-4a14-8129-fd2df220a834 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-04T09:41:11.471992Z digest=sha256:1c4ae26e9b4501f0cd30f84f42bd22e1b1dbc622822754d883f55f9f8df3ebdc

Observation e86360c2-cdf0-4e32-bd09-e06284885b02 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-04T09:41:11.543221Z digest=sha256:c9c50277ee2b22a13b87da0aec6f5919811f73fbbe170c6b6c11b86ed2b54a58

Observation 31cb9eb0-370d-4118-967b-f4e2d117e7e2 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-04T09:41:11.638192Z digest=sha256:6315ae0f534bc0016868dac282456c841986f316c3531c52a29ec1bec5f00a20

Observation 5b90168e-890d-4b2e-957d-b9a6257f78a6 · outbound

This paper cites A., & Thomas, R.

On leveraging constrained smooth additive regression models for global optimization A., & Thomas, R

Reference 7

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source=pdf_text observed=2026-08-04T09:41:11.701583Z digest=sha256:bb922c5ea0de55d9e4fc0d23ad390ee7b512357a1b5523a7a9036858d0c8030e

Observation f7892abb-593c-457a-814a-5cf98c85c5d1 · outbound

This paper cites T., Conn, A.

On leveraging constrained smooth additive regression models for global optimization T., Conn, A

Reference 8

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source=pdf_text observed=2026-08-04T09:41:11.793556Z digest=sha256:addcc4b902ebc814fb21c94176b1d946e1c65b21c839423c7f1b6b3d28bd9ce6

Observation 2499c305-65d2-47a8-8901-47d27ffcc3ae · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-04T09:41:11.882347Z digest=sha256:32317c9686aa62ffbab766b7766458ee93957685a8e8380cb794f0cdb7f35702

Observation 606d0254-ed26-4dae-98fc-6a40ff7e8257 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-04T09:41:11.992004Z digest=sha256:70414d929a2dd2ad0acea2987b6f3498994fd939c238dace9b4d62b3db6463fb

Observation 36cef204-1ab7-4cbb-9fbd-3c859d9a2709 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 11

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source=pdf_text observed=2026-08-04T09:41:12.048353Z digest=sha256:54ff9dd7f3d30d4323a26867247872ddacdcfa6f5b447f51a377bc101b477033

Observation 4357d58d-5e99-41a4-900d-1478ca643f1f · outbound

This paper cites R., Drud, A.

On leveraging constrained smooth additive regression models for global optimization R., Drud, A

Reference 12

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source=pdf_text observed=2026-08-04T09:41:12.119586Z digest=sha256:f5b05761d41a26807c9ea602962aecb7ab8c66a0d95073c7ed6a9343557e03fb

Observation 885ef4a9-cc6b-4452-8b28-3c2b5fe17518 · outbound

This paper cites U., & Gendron, B.

On leveraging constrained smooth additive regression models for global optimization U., & Gendron, B

Reference 13

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source=pdf_text observed=2026-08-04T09:41:12.202579Z digest=sha256:2c1bb59bceb49f35c8aadc043147eef6756ebcb4d81bd3ab45b23ed5f50b649f

Observation 4e7786b5-008c-4767-aaa3-23b477843e24 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 14

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source=pdf_text observed=2026-08-04T09:41:12.280644Z digest=sha256:8730cd48feaf42fa976e970ccc718babbcccb7a6ca886cff660a81bc71845f3e

Observation 4aecb2c9-2183-42e4-a84d-01f8e5e109fc · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 15

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source=pdf_text observed=2026-08-04T09:41:12.372450Z digest=sha256:f9cf34a19813fc38a4422e9c161e1c93905ff16f0cc769e5f7883fc496b7a230

Observation f5c4c4ce-b75c-45d8-9bf3-465063b6ac3c · outbound

This paper cites O., Maragno, D., & den Hertog, D.

On leveraging constrained smooth additive regression models for global optimization O., Maragno, D., & den Hertog, D

Reference 16

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source=pdf_text observed=2026-08-04T09:41:12.464739Z digest=sha256:a74914e0d919a3f4718b448e7bb79633dd4cd355491663ae0d8e37e00bbf1ae6

Observation 069754b0-c740-48ae-aeb2-4e8092e8a424 · outbound

This paper cites S., Karimi, I.

On leveraging constrained smooth additive regression models for global optimization S., Karimi, I

Reference 17

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Observation 0601de9f-0cc5-4dd2-8ee6-de305f409eed · outbound

This paper cites Parabolic Approximation & Relaxation for MINLP.

On leveraging constrained smooth additive regression models for global optimization Parabolic Approximation & Relaxation for MINLP

Reference 18

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Observation 65d607a3-9332-4b14-98ac-a5fc7c67c5e3 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-04T09:41:12.734940Z digest=sha256:8cda27fc73b4d2bb2c78a8283706cfe1a4b7f7549ef0965c8524f22202134260

Observation 36943e7e-9a7b-4490-b51f-aed146498363 · outbound

This paper cites I., den Hertog, D., & Fajemisin, A.

On leveraging constrained smooth additive regression models for global optimization I., den Hertog, D., & Fajemisin, A

Reference 20

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Observation 865c7ab2-bb84-42fa-a61f-cd1897414981 · outbound

This paper cites (2015, 10 1).

On leveraging constrained smooth additive regression models for global optimization (2015, 10 1)

Reference 21

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Observation 72b7a606-ec2a-4e1f-97c3-2a4ca7be61a5 · outbound

This paper cites S., & Sahinidis, N.

On leveraging constrained smooth additive regression models for global optimization S., & Sahinidis, N

Reference 22

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Observation f32be663-f650-49a7-9ea8-4ee911c8818c · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 23

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Observation 0cf6ea2c-2798-4dfd-a5a3-bb905631b533 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 24

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Observation 3975a806-47c8-47b0-98e0-f3ef391b23ea · outbound

This paper cites M., & Pantelides, C.

On leveraging constrained smooth additive regression models for global optimization M., & Pantelides, C

Reference 25

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Observation 8e117deb-fac7-4967-9d5e-ed1893da3a6e · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 26

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Observation 485a85f9-479c-4a65-911b-615ec0efc7ad · outbound

This paper cites (2017, 2).

On leveraging constrained smooth additive regression models for global optimization (2017, 2)

Reference 27

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Observation 64ae7210-5d96-4b01-b287-b6d867db6e09 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-04T09:41:13.432165Z digest=sha256:de530fb9ac45f9d80e7ea1cbb2300e5e637290637657965420ab996e89abfb81

Observation 5021660b-2697-4644-9fc4-97484e5adbd4 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 29

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source=pdf_text observed=2026-08-04T09:41:13.498759Z digest=sha256:400abe6cae4488b4ddb6b78a4e04cd88de7e3d7e8e6c648ea2af1c44b58fc9a9

Observation 0affce6f-152b-4ea9-a568-3d9b1b097f2f · outbound

This paper cites P., Ahmed, S., & Nemhauser, G.

On leveraging constrained smooth additive regression models for global optimization P., Ahmed, S., & Nemhauser, G

Reference 30

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Observation 9b40cd91-389c-4c30-8bff-68ddac2ace8f · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-04T09:41:13.645045Z digest=sha256:e4d39a717f99bc7eeb1f9e5a903efd04919fac053645157c1fab240960b065f5

Observation d96eb330-c7ad-43dd-b4b5-fe18ec029989 · outbound

This paper cites P., & Ormerod, J.

On leveraging constrained smooth additive regression models for global optimization P., & Ormerod, J

Reference 32

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Observation 8dfa67fd-d229-4166-9765-529d7d63473d · outbound

This paper cites A., & Rebennack, S.

On leveraging constrained smooth additive regression models for global optimization A., & Rebennack, S

Reference 33

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source=pdf_text observed=2026-08-04T09:41:13.818844Z digest=sha256:53734421406bf616433879b25be9ac0a48f81ec3686f63e77251916737f0c028

Observation 43338d53-1a51-4444-99f1-3c5b59337be2 · outbound

This paper cites an unresolved cited work.

On leveraging constrained smooth additive regression models for global optimization Unresolved cited work

Reference 34

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Pith citing papers

Observation 6e749e2d-cf54-4bf3-883a-9c0e7e5af96f · inbound

Automatic knot selection in smooth additive models cites this paper.

Automatic knot selection in smooth additive models On leveraging constrained smooth additive regression models for global optimization

Reference 1

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