Website stats and analysis
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mindmodeling.org was registered 1 decade 7 years ago. It has a alexa rank of #213,257 in the world. It is a domain having .org extension. It is estimated worth of $ 43,740.00 and have a daily income of around $ 81.00. As no active threats were reported recently, mindmodeling.org is SAFE to browse.

Traffic Report

Daily Unique Visitors: 7,195
Daily Pageviews: 28,780

Estimated Valuation

Income Per Day: $ 81.00
Estimated Worth: $ 43,740.00

Search Engine Indexes

Google Indexed Pages: Not Applicable
Yahoo Indexed Pages: Not Applicable
Bing Indexed Pages: Not Applicable

Search Engine Backlinks

Google Backlinks: Not Applicable
Bing Backlinks: Not Applicable
Alexa BackLinks: Not Applicable

Safety Information

Google Safe Browsing: No Risk Issues
Siteadvisor Rating: Not Applicable
WOT Trustworthiness: Very Poor
WOT Privacy: Very Poor
WOT Child Safety: Very Poor

Website Ranks & Scores

Alexa Rank: 213,257
PageSpeed Score: 89 ON 100
Domain Authority: 49 ON 100
Bounce Rate: Not Applicable
Time On Site: Not Applicable

Web Server Information

Hosted IP Address:

131.238.55.5

Hosted Country:

United States US

Location Latitude:

37.0586

Location Longitude:

-95.713

Traffic Classification

Total Traffic: No Data
Direct Traffic: No Data
Referral Traffic: No Data
Search Traffic: No Data
Social Traffic: No Data
Mail Traffic: No Data
Display Traffic: No Data

Search Engine Results For mindmodeling.org

A Novel Chunk-based Measure of Statistical Learning - CORE

- https://core.ac.uk/download/pdf/210795713.pdf

Abstract. Attempts to connect individual differences in statistical learning with broader aspects of cognition have received.


Can the High-Level Semantics of a Scene be Preserved in the Low ...

- https://voices.uchicago.edu/bermanlab/files/2019/10/44-Can-the-High-Level-Semantics-of-a-Scene-be-Preserved-in-the-Low-Level-Visual-Features-of-that-Scene_-A-Study-of-Disorder-and-Naturalness.pdf

Abstract. Real-world scenes contain low-level visual features (e.g., edges, colors) and high-level semantic features (e.g., objects and places).


simulating the confusing case of gender pronoun errors in L2 English

- http://mirjambroersma.nl/pdfs/Tsoukala_Frank_Broersma_2017.pdf

Even advanced Spanish speakers of second language English tend to confuse the pronouns 'he' and 'she', often without even noticing their mistake (Lahoz, ...


Incorporating Background Knowledge into Text Classification

- https://morteza-dehghani.net/wp-content/uploads/paper0052.pdf

Abstract. It has been shown that prior knowledge and information are organized according to categories, and that also background.


What Do We Learn from Rating Metaphors? - Computational ...

- https://www.coli.uni-saarland.de/~sikos/ThibodeauSikosDurgin_16.pdf

What makes some metaphors easier to understand than oth- ers? Theoretical accounts of metaphor processing appeal to dimensions like conventionality and ...


Explaining Enculturated Cognition

- http://www.ruhr-uni-bochum.de/mam/phil-lang/content/explaining_enculturated_cognition.pdf

Abstract. Many of our cognitive capacities are shaped by enculturation. Enculturation is the temporally extended transformative.


Maintenance of Perceptual Information in Speech Perception

- https://wbushong.github.io/publications/pub_files/paper0047.pdf

Acoustic and contextual cues to linguistic categories (e.g., phonemes or words) tend to be temporally distributed across the speech signal.


Scarcity impairs online detection and prospective memory

- https://zhaolab.psych.ubc.ca/pdfs/Tomm_Zhao_2017_CogSci.pdf

Abstract. Operating under limited resources poses significant demands on the cognitive system. Here we demonstrate that people under time scarcity failed to ...


Interindividual Skill Differences Predict Collective Benefit in...

- http://www.socsmcs.eu/system/files/PublicFiles/paper0473.pdf

Abstract. When two individuals perform a task together, they combine their individual skills to achieve a joint goal. Previous.


Can Generic Neural Networks Estimate Numerosity Like Humans?

- https://stanford.edu/~jlmcc/papers/ChenZhouFangMcC18Estimation.pdf

implemented in TensorFlow (https://www.tensorflow.org/). The network is a recurrent neural network that can learn to direct its attention while attempting ...


MindModeling@Home

- https://mindmodeling.org/

MindModeling@Home is a research project that uses volunteer computing for the advancement of cognitive science. The research focuses on utilizing computational ...


A theoretically driven meta-analysis of implicit theory of mind...

- https://cognitivesciencesociety.org/cogsci20/papers/0387/0387.pdf

The capacity for Theory of Mind (ToM) allows us to repre- sent others' understanding of the world independently from our own and then explain and predict ...


41st CogSci 2019: Montreal, Canada - DBLP

- https://dblp.org/db/conf/cogsci/cogsci2019

... 2019: Creativity + Cognition + Computation, Montreal, Canada, July 24-27, 2019. cognitivesciencesociety.org 2019, ISBN 0-9911967-7-5 text to speech ...


Publications | Emily Morgan, Ph.D. - Tufts

- https://sites.tufts.edu/emilymorgan/publications/

Available online: http://mindmodeling.org/cogsci2015/papers/0287/paper0287.pdf. Morgan, E., Keller, F., and Steedman, M. (2010). A Bottom-up Parsing Model ...


Science United

- https://scienceunited.org/su_science.php

Web site: https://mindmodeling.org/. MindModeling@Home uses computational cognitive process modeling to better understand the human mind, and specifically ...


Prediction and uncertainty in an artificial language ∑ - Tal Linzen

- https://tallinzen.net/media/papers/linzen_siegelman_bogaerts_2017_cogsci.pdf

Probabilistic prediction is a central process in language com- prehension. Properties of probability distributions over predic-.


What if? Counterfactual reasoning, pretense, and the role of ...

- https://www.research.ed.ac.uk/en/publications/what-if-counterfactual-reasoning-pretense-and-the-role-of-possibl

69-70) https://mindmodeling.org/cogsci2013/papers/0026/index.html. Buchsbaum, Daphna ; Walker, Caren M. ; Gopnik, Alison ; Chater, Nick ; Danks, ...


(PDF) Learning How To Throw Darts: The Effect Of Modeling Type ...

- https://www.researchgate.net/publication/331036568_Learning_How_To_Throw_Darts_The_Effect_Of_Modeling_Type_And_Reflection_On_Dart-Throwing_Skills

12 февр. 2019 г. ... PDF | In this study we investigate the effect of modeling type and reflection on the acquisition of dart-throwing skills, self-efficacy ...


Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks

- https://aclanthology.org/2021.emnlp-main.85

To enable theory of mind modeling in situated interactions, we introduce a fine-grained ... Language: URL: https://aclanthology.org/2021.emnlp-main.85 ...


Predicting cognitive difficulty of the deductive mastermind game...

- https://research.vu.nl/en/publications/predicting-cognitive-difficulty-of-the-deductive-mastermind-game-

[0527] Cognitive Science Society. https://mindmodeling.org/cogsci2018/papers/0527/index.html. Zhao, Bonan ; van de Pol, Iris ; Raijmakers, ...


Naïve Physics - the wrong theory?

- https://ore.exeter.ac.uk/repository/handle/10871/18054

http://mindmodeling.org/cogsci2013/papers/0199/index.html. Abstract. In this paper we examine the idea of a "naïve physics" in humans solving physics ...


Publications | Cognitive Science & Numeracy Lab

- https://www.cogscinumeracy.com/publications

1150–1155). Austin, TX: Cognitive Science Society. ​. https://mindmodeling.org/cogsci2017/papers/0222 ...

Page Resources Breakdown

Homepage Links Analysis

MindModeling@Home

Website Inpage Analysis

H1 Headings: 1 H2 Headings: Not Applicable
H3 Headings: Not Applicable H4 Headings: Not Applicable
H5 Headings: Not Applicable H6 Headings: Not Applicable
Total IFRAMEs: Not Applicable Total Images: 73
Google Adsense: Not Applicable Google Analytics: Not Applicable

HTTP Header Analysis

Http-Version: 1.1
Status-Code: 200
Status: 200 OK
Server: nginx
Date: Sun, 12 Jun 2022 10:00:21 GMT
Content-Type: text/html; charset=UTF-8
Transfer-Encoding: chunked
Connection: keep-alive
Content-Encoding: gzip

Domain Information

Domain Registrar: Public Interest Registry
Registration Date: 2007-03-10 1 decade 7 years 8 months ago

Domain Nameserver Information

Host IP Address Country
ns37.domaincontrol.com 97.74.108.19 United States United States
ns38.domaincontrol.com 173.201.76.19 United States United States

DNS Record Analysis

Host Type TTL Extra
mindmodeling.org A 1784 IP: 131.238.55.5
mindmodeling.org NS 3600 Target: ns38.domaincontrol.com
mindmodeling.org NS 3600 Target: ns37.domaincontrol.com
mindmodeling.org SOA 3600 MNAME: NS37.DOMAINCONTROL.COM
RNAME: dns.jomax.net
Serial: 2022041500
Refresh: 28800
Retry: 7200
Expire: 604800
mindmodeling.org MX 3600 Target: udri.mindmodeling.org

Full WHOIS Lookup

Domain Name: mindmodeling.org
Registry Domain ID:
721cc0c4620a455db91bb31adc709c02-LROR
Registrar WHOIS Server:
whois.godaddy.com
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Updated Date:
2022-06-02T21:39:00Z
Creation Date:
2007-03-09T19:29:33Z
Registry Expiry Date:
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Registrar: GoDaddy.com, LLC
Registrar
IANA ID: 146
Registrar Abuse Contact Email:
[email protected]
Registrar Abuse Contact Phone:
+1.4806242505
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