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Paper Citation Record · LEDGER

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data

As of 9 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.03224.

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pith.paper-citation-record.v1
2506.03224 v1

Coverage vector

measured 45 of 45 reference resolution

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measured 45 of 45 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

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External citation measurements

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Outbound references

Observation 76ad7882-267e-40b6-a0cb-9d79e26e9504 · outbound

This paper cites Paris agreement.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Paris agreement

Reference 1

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Observation 6c43aef9-00f7-4122-a261-b39ae67019a2 · outbound

This paper cites High resolution fossil fuel combustion co2 emission fluxes for the united states.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data High resolution fossil fuel combustion co2 emission fluxes for the united states

Reference 13

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Observation 8b855dd2-1af1-4c20-ac6d-be8c5956d4a2 · outbound

This paper cites The vulcan version 3.0 high-resolution fossil fuel co2 emis- sions for the united states.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data The vulcan version 3.0 high-resolution fossil fuel co2 emis- sions for the united states

Reference 14

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Observation c61702a2-f091-46f3-96fd-4ca382bc4489 · outbound

This paper cites The effects of urban agglomeration economies on carbon emissions: Evidence from chinese cities.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data The effects of urban agglomeration economies on carbon emissions: Evidence from chinese cities

Reference 15

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Observation bd4e44ce-56f0-4990-b291-2935c29b6d33 · outbound

This paper cites Lightweight and robust representation of economic scales from satellite imagery.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Lightweight and robust representation of economic scales from satellite imagery

Reference 16

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Observation bbe27e86-aedd-4fde-8d3e-321b87164dcc · outbound

This paper cites Deep residual learning for image recog- nition.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Deep residual learning for image recog- nition

Reference 17

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Observation 12cf7734-2272-4a14-ad7e-f5495e99d7b3 · outbound

This paper cites Squeeze- and-excitation networks.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Squeeze- and-excitation networks

Reference 18

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Observation a3a2ac86-c313-43c5-b872-bd0b76246a41 · outbound

This paper cites A comparison of five high-resolution spatially-explicit, fossil-fuel, carbon diox- ide emission inventories for the united states.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data A comparison of five high-resolution spatially-explicit, fossil-fuel, carbon diox- ide emission inventories for the united states

Reference 19

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Observation 0cc50a99-9af3-4339-a17c-33366215f844 · outbound

This paper cites Predicting transportation carbon emission with urban big data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Predicting transportation carbon emission with urban big data

Reference 22

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Observation 2f4424f4-0cb0-41e1-a529-2cea74837be9 · outbound

This paper cites Management and estimation of thermal comfort, carbon dioxide emission and economic growth by support vector machine.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Management and estimation of thermal comfort, carbon dioxide emission and economic growth by support vector machine

Reference 23

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Observation aad4a695-a01b-4bd2-baf0-8d8105dafbf7 · outbound

This paper cites A global review of energy consumption, co2 emissions and policy in the residential sector (with an overview of the top ten co2 emitting countries).

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data A global review of energy consumption, co2 emissions and policy in the residential sector (with an overview of the top ten co2 emitting countries)

Reference 24

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This paper cites an unresolved cited work.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Unresolved cited work

Reference 25

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Observation 57281d6b-1367-43ff-92dc-20d087694106 · outbound

This paper cites Emission database for global atmospheric research (edgar).

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Emission database for global atmospheric research (edgar)

Reference 26

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Observation 41ae792d-e86f-4c25-ada2-ef30eab33db9 · outbound

This paper cites Carbon accounting: a systematic literature review.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Carbon accounting: a systematic literature review

Reference 29

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Observation 3f6adbe2-ced9-4b07-adc8-3d3e4704c6bd · outbound

This paper cites Carbon emission from urban passenger transporta- tion in beijing.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Carbon emission from urban passenger transporta- tion in beijing

Reference 31

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Observation a17590fc-8e8a-45c2-ad77-2dcde3134f82 · outbound

This paper cites Crime rate inference with big data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Crime rate inference with big data

Reference 32

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Observation 095ce68a-e7dd-4608-ba5a-8a274ec2c09d · outbound

This paper cites Agglomeration effect of co2 emissions and emissions reduc- tion effect of technology: A spatial econometric perspective based on china’s province-level data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Agglomeration effect of co2 emissions and emissions reduc- tion effect of technology: A spatial econometric perspective based on china’s province-level data

Reference 33

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Observation d90951d1-ef0f-4309-b4f6-048d539182b2 · outbound

This paper cites The effect of urbanization and spatial agglomeration on carbon emissions in urban ag- glomeration.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data The effect of urbanization and spatial agglomeration on carbon emissions in urban ag- glomeration

Reference 34

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Observation d86a88a4-d762-44af-be20-ca755939a8d1 · outbound

This paper cites High-resolution mapping of regional traffic emissions using land-use ma- chine learning models.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data High-resolution mapping of regional traffic emissions using land-use ma- chine learning models

Reference 35

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Observation 8fcf1c60-dcc3-493b-b85d-3e01d0415fd8 · outbound

This paper cites Beyond the first law of geography: Learning representations of satellite imagery by leveraging point-of-interests.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Beyond the first law of geography: Learning representations of satellite imagery by leveraging point-of-interests

Reference 36

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Observation d541dbe5-ea17-43a6-a6d2-6ff23bce5d77 · outbound

This paper cites Ar2net: An attentive neural approach for business location selection with satellite data and urban data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Ar2net: An attentive neural approach for business location selection with satellite data and urban data

Reference 37

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Observation bbcae22f-ddab-4710-9f08-714c61730131 · outbound

This paper cites Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery

Reference 38

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Observation f7b233c1-1820-4fb6-8104-c90d312f3dc9 · outbound

This paper cites Using publicly available satellite imagery and deep learning to understand economic well-being in africa.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Using publicly available satellite imagery and deep learning to understand economic well-being in africa

Reference 39

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Observation 462baf2f-635b-448e-a9ea-d6c6381b46c8 · outbound

This paper cites Smartphone app usage pre- diction using points of interest.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Smartphone app usage pre- diction using points of interest

Reference 40

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This paper cites Household carbon emission research: an analyt- ical review of measurement, influencing factors and miti- gation prospects.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Household carbon emission research: an analyt- ical review of measurement, influencing factors and miti- gation prospects

Reference 41

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Observation 53549bbb-5a9f-4f39-a913-35e16d9d8f5f · outbound

This paper cites Towards low carbon cities: A machine learning method for predicting urban blocks carbon emissions (ubce) based on built environment factors (bef) in changxing city, china.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Towards low carbon cities: A machine learning method for predicting urban blocks carbon emissions (ubce) based on built environment factors (bef) in changxing city, china

Reference 42

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Observation 7f794ccf-9f12-4021-9f3c-c8cb242a8aed · outbound

This paper cites Estimating global anthropogenic co2 gridded emissions using a data-driven stacked random for- est regression model.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Estimating global anthropogenic co2 gridded emissions using a data-driven stacked random for- est regression model

Reference 43

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Source-reported events for the cited work

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Observation 7b670831-30e9-49d8-b26f-76c94f1000a0 · outbound

This paper cites Identifying urban functional re- gions from high-resolution satellite images using a context- aware segmentation network.Remote Sensing, 14(16):3996,.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Identifying urban functional re- gions from high-resolution satellite images using a context- aware segmentation network.Remote Sensing, 14(16):3996,

Reference 44

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Observation 375cfe0c-0836-42ee-8636-5ef1868d469f · outbound

This paper cites Assessing osm building complete- ness for almost 13,000 cities globally.International Journal of Digital Earth, 15(1):2400–2421, 2022.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Assessing osm building complete- ness for almost 13,000 cities globally.International Journal of Digital Earth, 15(1):2400–2421, 2022

Reference 45

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Observation c7531b99-e055-498d-b563-1cf1dbc87775 · outbound

This paper cites A 1990 global emission inventory of anthro- pogenic sources of carbon monoxide on 1× 1 developed in the framework of edgar/geia.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data A 1990 global emission inventory of anthro- pogenic sources of carbon monoxide on 1× 1 developed in the framework of edgar/geia

Reference 1994

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Observation e87f76ba-ec1c-4409-933b-108e8f93ca7a · outbound

This paper cites China high resolution emission database (chred) with point emission sources, gridded emission data, and supplemen- tary socioeconomic data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data China high resolution emission database (chred) with point emission sources, gridded emission data, and supplemen- tary socioeconomic data

Reference 1998

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:04.271223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 185fcbc0-3043-48fa-a37c-48f6c8ecf1e4 · outbound

This paper cites Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning

Reference 1999

Resolution
unresolved
no resolver link, observed 2026-08-07T11:21:55.993906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 03f32a75-adab-42a6-b28d-640d47da93d8 · outbound

This paper cites The synthesis of bottom-up and top-down in energy policy modeling.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data The synthesis of bottom-up and top-down in energy policy modeling

Reference 2008

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:04.495552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b9f29359-7fc9-42b0-ac4c-14b840d6298a · outbound

This paper cites Understanding urban functionality from poi space.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Understanding urban functionality from poi space

Reference 2009

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:02.875884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 11fc383d-ceeb-4509-af9a-a56f89c77bcb · outbound

This paper cites A simple framework for con- trastive learning of visual representations.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data A simple framework for con- trastive learning of visual representations

Reference 2011

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8f753b77-a18f-4f6a-9c0c-987081c2347e · outbound

This paper cites Visualizing data using t-sne.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Visualizing data using t-sne

Reference 2012

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d5324a2a-bcf3-403b-aeb2-75bd27e17ff7 · outbound

This paper cites Machine learn- ing and phone data can improve targeting of humanitarian aid.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Machine learn- ing and phone data can improve targeting of humanitarian aid

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:05.081102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e8b7135a-c1f9-4bda-9c74-3ee7072a2683 · outbound

This paper cites Urban energy use and car- bon emissions from cities in china and policy implications.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Urban energy use and car- bon emissions from cities in china and policy implications

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:03.062745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e2ca980f-7e7e-4e16-b182-b8a04fda3493 · outbound

This paper cites Tile2vec: Unsupervised representation learning for spatially dis- tributed data.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Tile2vec: Unsupervised representation learning for spatially dis- tributed data

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:01.514989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:21:55.205599Z digest=sha256:dc2dd785d8070241d68bd10a8676642e7c84c7b054b9e87ff60bada7d8636f2a

Observation 2ff1a19a-d76f-4d89-a9a7-7b010f54be7f · outbound

This paper cites Introduction to remote sensing.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Introduction to remote sensing

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:04.038738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:21:53.936694Z digest=sha256:c177cb5bf3bdb240e8ed501ad508962f64888acebd67db942f15b1dcac432c3b

Observation 587048ef-db48-467e-a112-06ef62fdabc6 · outbound

This paper cites Carbon monitor, a near-real- time daily dataset of global co2 emission from fossil fuel and cement production.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Carbon monitor, a near-real- time daily dataset of global co2 emission from fossil fuel and cement production

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:01.275356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:21:55.324500Z digest=sha256:75db167ea9c1a5bd2ba69ae528d9216073fe9b0263b1c5109a7dfaa5b6d336bb

Observation 60c24adc-49af-4454-869f-be279f97a96d · outbound

This paper cites Spatiotemporal prediction of carbon emissions using a hybrid deep learn- ing model considering temporal and spatial correlations.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Spatiotemporal prediction of carbon emissions using a hybrid deep learn- ing model considering temporal and spatial correlations

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:03.543210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a55c3857-5254-442a-8532-b4396a0707e1 · outbound

This paper cites Combining bottom-up and top-down.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Combining bottom-up and top-down

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:04.694369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:21:53.617410Z digest=sha256:3a106808a1a29bd9edb62b58f46a911faf6220dcc9da45ec2e3e02761603e3ed

Observation cc974e3d-fe5b-4bc2-916e-adf27ce41db8 · outbound

This paper cites Advancing climate action and resilience through an urban lens,.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Advancing climate action and resilience through an urban lens,

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:04.869426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 419cfaef-903a-4972-b179-08b9a5d720ca · outbound

This paper cites Closing the gap? top-down versus bottom-up projections of china’s regional energy use and co2 emissions.

OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data Closing the gap? top-down versus bottom-up projections of china’s regional energy use and co2 emissions

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:22:03.294482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

No inbound Pith citation observations are available.