Pith. sign in

Paper Citation Record · LEDGER

Bayesian network approach to building an affective module for a driver behavioural model

As of 24 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2502.03254.

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

pith.paper-citation-record.v1
2502.03254 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:24:44.837738Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42cab1c1-c891-4f1e-b1cd-29a3e4216ea0 · outbound

This paper cites From Bayesian Networks to Causal Networks.

Bayesian network approach to building an affective module for a driver behavioural model From Bayesian Networks to Causal Networks

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.999310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.792070Z digest=sha256:e2b893e8c23c0098f06a39c1e52a2cec30b17fc124cbe3116973d9dac4f272ba

Observation b964ce90-23d4-424e-aa6f-85c9798e65cf · outbound

This paper cites Bayesian Networks,.

Bayesian network approach to building an affective module for a driver behavioural model Bayesian Networks,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.988957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.796571Z digest=sha256:bf7f5361e76bee11246833bdb1ba16ed89ec4d134122c5110a512a2f9e57eec5

Observation f647f9fa-4f58-499f-bc81-5e2af5503518 · outbound

This paper cites The BATmobile: Towards a Bayesian automated taxi,.

Bayesian network approach to building an affective module for a driver behavioural model The BATmobile: Towards a Bayesian automated taxi,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.978844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.800676Z digest=sha256:65d5844d70f8f85676cef0393ef4e9dda55e1a5a27d46044764587e2e4667fd3

Observation 73fd8fc2-a0c5-43ea-bbee-2d9aabac3966 · outbound

This paper cites Driver Behavior Modeling Toward Au- tonomous Vehicles: Comprehensive Review,.

Bayesian network approach to building an affective module for a driver behavioural model Driver Behavior Modeling Toward Au- tonomous Vehicles: Comprehensive Review,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.968870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.804304Z digest=sha256:84cef44ecb14d734d63cdd65f6e7c22276ba30a2933149c58693e25ebde47bea

Observation e20d6ad5-4dbf-48d9-9edb-3e6732e1b39d · outbound

This paper cites A model for reasoning about persistence and causation,.

Bayesian network approach to building an affective module for a driver behavioural model A model for reasoning about persistence and causation,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.958707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.808199Z digest=sha256:8226814853c389b838b02106f61781e0cb59419c023dfd63398b047c5e80d9e9

Observation 74314e7b-c29a-4bbc-afa0-84c8b0ce4a27 · outbound

This paper cites Core Statistics.

Bayesian network approach to building an affective module for a driver behavioural model Core Statistics

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.948394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.812351Z digest=sha256:38afa4dad18774441f4f9da62166e904fa221e42340c9fcb29911c93a1d060a7

Observation 2fdee421-159c-4d86-b149-389a2d146da0 · outbound

This paper cites Quantification of uncertainty and its applications to complex domain for autonomous vehicles percep- tion system,.

Bayesian network approach to building an affective module for a driver behavioural model Quantification of uncertainty and its applications to complex domain for autonomous vehicles percep- tion system,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.938090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.816491Z digest=sha256:af56052cdddc8556e0ae4777f17cd00d45605716435a7a47a20ea0406f265ae3

Observation 49d60510-ba7b-459a-b47c-9a1304add4f0 · outbound

This paper cites The analysis of driver’s behavioral tendency under different emotional states based on a Bayesian network,.

Bayesian network approach to building an affective module for a driver behavioural model The analysis of driver’s behavioral tendency under different emotional states based on a Bayesian network,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.927211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.820135Z digest=sha256:f03602f57be1c41b97de5850166d2e2691fd3f0d5a208bb2a1f14dcc7e300410

Observation ee0bfa33-0dd2-49ca-9c71-be7576e93e60 · outbound

This paper cites Driver fatigue evaluation model with integration of multi-indicators based on dynamic Bayesian network,.

Bayesian network approach to building an affective module for a driver behavioural model Driver fatigue evaluation model with integration of multi-indicators based on dynamic Bayesian network,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.915628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.823717Z digest=sha256:1467d03bd766e5382b2e4d0c65b56a0f867b4423a3a867db7d8119966708e3b9

Observation 2e1524dc-1053-489c-989e-83d573e4c776 · outbound

This paper cites A driver fatigue recognition model based on information fusion and dynamic Bayesian network,.

Bayesian network approach to building an affective module for a driver behavioural model A driver fatigue recognition model based on information fusion and dynamic Bayesian network,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.903383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.827379Z digest=sha256:3d19bd079cd6b9b3cc4b87b0ff78b04205c45b9919662522da30930632414ae4

Observation d43ee1f0-3b43-4078-acff-f13b4b242631 · outbound

This paper cites and Pivik, K., ”Age and gender differences in risky driving: the roles of positive affect and risk perception,” *Accid.

Bayesian network approach to building an affective module for a driver behavioural model and Pivik, K., ”Age and gender differences in risky driving: the roles of positive affect and risk perception,” *Accid

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.891806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.830844Z digest=sha256:735fac423e451141428f38fcb19d72b127b9c5b5adea798586414ff94fd2cc00

Observation 6d8d70bc-b8de-47e7-8fbd-23d5bcb879bd · outbound

This paper cites Learning Bayesian Networks with the bnlearn R Package,.

Bayesian network approach to building an affective module for a driver behavioural model Learning Bayesian Networks with the bnlearn R Package,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.880930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.834313Z digest=sha256:9d18f1409e4f406a079ac1f30ded2863919013425eb4ade16e639bd2947e0e9f

Observation 63359bb0-7f1d-4f7b-9787-87953758a41b · outbound

This paper cites The Bayesian information criterion: Background, derivation, and applications,.

Bayesian network approach to building an affective module for a driver behavioural model The Bayesian information criterion: Background, derivation, and applications,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T05:24:44.869308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T05:24:44.837738Z digest=sha256:cf7aad00aa9af8fe36850d11dec9606cd104e42eb459bccfdfe70416c22f8b26

Pith citing papers

No inbound Pith citation observations are available.