Paper Citation Record · LEDGER

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection

As of 14 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2601.18295.

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

pith.paper-citation-record.v1
2601.18295 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T11:26:15.596039Z

measured 24 of 24 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 2026-05-16T11:26:15.596039Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-16T11:27:48.200600Z

Reference resolution

23 of 23 outbound references displayed

verified exact3
verified fuzzy16
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d8d8376-ec8d-484c-b04e-185f02d08182 · outbound

This paper cites Coronary artery disease (CAD) is the largest subtype.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Coronary artery disease (CAD) is the largest subtype

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.694099Z

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.

Observation 262ca34f-15ee-4986-9c65-b760ba7a7e55 · outbound

This paper cites Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-16T11:27:48.202379Z

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.

Observation 45a2ad6f-bd1e-4618-a222-42ee221a5236 · outbound

This paper cites The methods will first detail the novel energy-based noisy segment rejection approach, preprocessing, and feature extraction before detailing the model training and inference.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection The methods will first detail the novel energy-based noisy segment rejection approach, preprocessing, and feature extraction before detailing the model training and inference

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.686981Z

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.

Observation 657a020d-8772-466a-9435-b9cdc56c1682 · outbound

This paper cites an unresolved cited work.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-05-16T11:27:48.675449Z

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.

Observation 30a8ce22-86f3-4078-9711-ac8129df3ebe · outbound

This paper cites Future work will include ablations and cross-dataset ex- periments to better quantify component contributions and generalisation.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Future work will include ablations and cross-dataset ex- periments to better quantify component contributions and generalisation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.673137Z

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.

Observation 81f3bf32-dfe9-4d95-8cda-b58861566807 · outbound

This paper cites an unresolved cited work.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-16T11:27:48.670713Z

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.

Observation 20acad30-6b30-4dc8-9d69-d6e424e6f686 · outbound

This paper cites Cardiac auscultation: Rediscovering the lost art.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Cardiac auscultation: Rediscovering the lost art

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.677502Z

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.

Observation e8e909a5-4f0b-41da-b01a-770028a40f4d · outbound

This paper cites The Lost Art of clinical skills.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection The Lost Art of clinical skills

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.667027Z

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.

Observation f22e7767-45f5-4e13-b354-b73319df31f2 · outbound

This paper cites Accuracy of cardiac auscultation in detection of neonatal congenital heart disease by general paedi- atricians.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Accuracy of cardiac auscultation in detection of neonatal congenital heart disease by general paedi- atricians

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.691709Z

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.

Observation f2924a1a-cd0c-4557-9995-954858ac8898 · outbound

This paper cites an unresolved cited work.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-05-16T11:27:48.680097Z

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.

Observation fa8f2bf7-d5d0-43a1-89e8-8a33eb770055 · outbound

This paper cites Available: https://www.sciencedirect.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Available: https://www.sciencedirect

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.668834Z

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.

Observation 054ad0e7-2953-467b-bb93-132c11a62396 · outbound

This paper cites Practicality meets precision: Wearable vest with integrated multi-channel pcg sensors for effec- tive coronary artery disease pre-screening.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Practicality meets precision: Wearable vest with integrated multi-channel pcg sensors for effec- tive coronary artery disease pre-screening

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.658107Z

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.

Observation 43a708a7-12c9-4cf5-b16d-43a785002ebd · outbound

This paper cites Enhancing cross-domain robustness in phonocardiogram signal classification using domain-invariant preprocessing and transfer learning.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Enhancing cross-domain robustness in phonocardiogram signal classification using domain-invariant preprocessing and transfer learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.660458Z

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.

Observation b82d115c-6b74-42d2-be65-b77c61d014d0 · outbound

This paper cites An improved method to detect coronary artery disease using phonocardiogram signals in noisy en- vironment.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection An improved method to detect coronary artery disease using phonocardiogram signals in noisy en- vironment

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.662787Z

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.

Observation e90e7a14-b0f8-4f11-afa5-4dd8c0fc7373 · outbound

This paper cites Available: https://www.sciencedirect.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Available: https://www.sciencedirect

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.653750Z

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.

Observation 6799d9a5-7ce7-48e8-8d67-09f0c696cfcd · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T11:27:48.195077Z

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.

Observation cb2e0618-febf-4214-b328-aa7e19a3770c · outbound

This paper cites A comprehensive survey on heart sound analysis in the deep learning era.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection A comprehensive survey on heart sound analysis in the deep learning era

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.682251Z

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.

Observation eab3141c-0b9e-44d7-b030-cfab7cd42ec5 · outbound

This paper cites Risk factors for coronary artery disease: his- torical perspectives.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Risk factors for coronary artery disease: his- torical perspectives

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.684405Z

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.

Observation 8d48dec5-ab18-4a58-aa02-094c0ff6d527 · outbound

This paper cites Acoustic features for the identification of coronary artery disease.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Acoustic features for the identification of coronary artery disease

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.665143Z

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.

Observation f87584f8-cf93-484a-9500-d081dd3f4656 · outbound

This paper cites Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:17:06.472641Z

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.

Observation f5ff3d86-ae6a-46a7-91f2-370dad4258b3 · outbound

This paper cites Decoupled Weight Decay Regularization.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Decoupled Weight Decay Regularization

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-16T11:27:48.191526Z

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.

Observation b460af32-eb78-4d9a-855a-f37684f03ee2 · outbound

This paper cites The advantages of the matthews correlation coefficient (MCC) over f1 score and accuracy in binary classification evaluation.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection The advantages of the matthews correlation coefficient (MCC) over f1 score and accuracy in binary classification evaluation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.689147Z

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.

Observation 2528d23e-51c6-411d-a19e-cf1a0be8bd4b · outbound

This paper cites Optuna: A next-generation hyperparameter optimiza- tion framework.

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection Optuna: A next-generation hyperparameter optimiza- tion framework

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T11:27:48.655996Z

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.

Pith citing papers

Observation 262ca34f-15ee-4986-9c65-b760ba7a7e55 · inbound