A citation-based method for searching scientific literature

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks.
Samantha M W Wood, Justin N Wood. Infant Behav Dev 2019
Times Cited: 6






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List of co-cited articles
22 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Newborn chickens generate invariant object representations at the onset of visual object experience.
Justin N Wood. Proc Natl Acad Sci U S A 2013
27
4
66

A smoothness constraint on the development of object recognition.
Justin N Wood. Cognition 2016
7
3
50

The development of newborn object recognition in fast and slow visual worlds.
Justin N Wood, Samantha M W Wood. Proc Biol Sci 2016
10
3
50

Newly hatched chicks solve the visual binding problem.
Justin N Wood. Psychol Sci 2014
16
3
50

Enhanced learning of natural visual sequences in newborn chicks.
Justin N Wood, Aditya Prasad, Jason G Goldman, Samantha M W Wood. Anim Cogn 2016
9
3
50

Slow feature analysis: unsupervised learning of invariances.
Laurenz Wiskott, Terrence J Sejnowski. Neural Comput 2002
213
3
50

The persistent sampling bias in developmental psychology: A call to action.
Mark Nielsen, Daniel Haun, Joscha Kärtner, Cristine H Legare. J Exp Child Psychol 2017
206
2
33

False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.
Joseph P Simmons, Leif D Nelson, Uri Simonsohn. Psychol Sci 2011
1834
2
33

Using automatic face analysis to score infant behaviour from video collected online.
Brea Chouinard, Kimberly Scott, Rhodri Cusack. Infant Behav Dev 2019
12
2
33

A Collaborative Approach to Infant Research: Promoting Reproducibility, Best Practices, and Theory-Building.
Michael C Frank, Elika Bergelson, Christina Bergmann, Alejandrina Cristia, Caroline Floccia, Judit Gervain, J Kiley Hamlin, Erin E Hannon, Melissa Kline, Claartje Levelt,[...]. Infancy 2017
71
2
33

Power failure: why small sample size undermines the reliability of neuroscience.
Katherine S Button, John P A Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma S J Robinson, Marcus R Munafò. Nat Rev Neurosci 2013
2976
2
33

Publication standards in infancy research: Three ways to make Violation-of-Expectation studies more reliable.
Paula Rubio-Fernández. Infant Behav Dev 2019
10
2
33

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
580
2
33

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.
Edmund T Rolls. Front Comput Neurosci 2012
70
2
33

The Development of Invariant Object Recognition Requires Visual Experience With Temporally Smooth Objects.
Justin N Wood, Samantha M W Wood. Cogn Sci 2018
6
2
33

Face recognition in newly hatched chicks at the onset of vision.
Samantha M W Wood, Justin N Wood. J Exp Psychol Anim Learn Cogn 2015
8
2
33

Learning Invariance from Transformation Sequences.
Peter Földiák. Neural Comput 1991
244
2
33

Characterizing the information content of a newly hatched chick's first visual object representation.
Justin N Wood. Dev Sci 2015
15
2
33

Effects of temporal association on recognition memory.
G Wallis, H H Bülthoff. Proc Natl Acad Sci U S A 2001
121
2
33

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
374
2
33

A chicken model for studying the emergence of invariant object recognition.
Samantha M W Wood, Justin N Wood. Front Neural Circuits 2015
15
2
33

Measuring the speed of newborn object recognition in controlled visual worlds.
Justin N Wood, Samantha M W Wood. Dev Sci 2017
4
2
50

False belief in infancy: a fresh look.
Cecilia Heyes. Dev Sci 2014
100
1
16

Making replication mainstream.
Rolf A Zwaan, Alexander Etz, Richard E Lucas, M Brent Donnellan. Behav Brain Sci 2017
88
1
16

Reliability and generalizability of an acted-out false belief task in 3-year-olds.
Sebastian Dörrenberg, Lisa Wenzel, Marina Proft, Hannes Rakoczy, Ulf Liszkowski. Infant Behav Dev 2019
5
1
20

Changing institutional incentives to foster sound scientific practices: One department.
Rebecca A Lundwall. Infant Behav Dev 2019
2
1
50

Infants' perception of goal-directed actions: A multi-lab replication reveals that infants anticipate paths and not goals.
Kerstin Ganglmayer, Manja Attig, Moritz M Daum, Markus Paulus. Infant Behav Dev 2019
10
1
16

PyHab: Open-source real time infant gaze coding and stimulus presentation software.
Jonathan F Kominsky. Infant Behav Dev 2019
9
1
16

Should I test more babies? Solutions for transparent data peeking.
Esther Schott, Mijke Rhemtulla, Krista Byers-Heinlein. Infant Behav Dev 2019
6
1
16

PSYCHOLOGY. Estimating the reproducibility of psychological science.
. Science 2015
1910
1
16

Promoting Replicability in Developmental Research Through Meta-analyses: Insights From Language Acquisition Research.
Christina Bergmann, Sho Tsuji, Page E Piccinini, Molly L Lewis, Mika Braginsky, Michael C Frank, Alejandrina Cristia. Child Dev 2018
45
1
16

Online recruitment and testing of infants with Mechanical Turk.
Michelle Tran, Laura Cabral, Ronak Patel, Rhodri Cusack. J Exp Child Psychol 2017
21
1
16

Psychology, Science, and Knowledge Construction: Broadening Perspectives from the Replication Crisis.
Patrick E Shrout, Joseph L Rodgers. Annu Rev Psychol 2018
99
1
16

False-belief understanding in infants.
Renée Baillargeon, Rose M Scott, Zijing He. Trends Cogn Sci 2010
283
1
16

Eurosibs: Towards robust measurement of infant neurocognitive predictors of autism across Europe.
E J H Jones, L Mason, J Begum Ali, C van den Boomen, R Braukmann, E Cauvet, E Demurie, R S Hessels, E K Ward, S Hunnius,[...]. Infant Behav Dev 2019
12
1
16

Probing communication-induced memory biases in preverbal infants: Two replication attempts of Yoon, Johnson and Csibra (2008).
Priya Silverstein, Teodora Gliga, Gert Westermann, Eugenio Parise. Infant Behav Dev 2019
7
1
16

An overview of issues in infant and developmental research for the creation of robust and replicable science.
Pamela E Davis-Kean, Alexa Ellis. Infant Behav Dev 2019
8
1
16

Reproducibility and a unifying explanation: Lessons from the shape bias.
Sarah C Kucker, Larissa K Samuelson, Lynn K Perry, Hanako Yoshida, Eliana Colunga, Megan G Lorenz, Linda B Smith. Infant Behav Dev 2019
6
1
16

33-month-old children succeed in a false belief task with reduced processing demands: A replication of Setoh et al. (2016).
Stella S Grosso, Tobias Schuwerk, Larissa J Kaltefleiter, Beate Sodian. Infant Behav Dev 2019
10
1
16

A hierarchy of time-scales and the brain.
Stefan J Kiebel, Jean Daunizeau, Karl J Friston. PLoS Comput Biol 2008
330
1
16

Sequence learning in infancy: the independent contributions of conditional probability and pair frequency information.
Stuart Marcovitch, David J Lewkowicz. Dev Sci 2009
27
1
16

An automated controlled-rearing method for studying the origins of movement recognition in newly hatched chicks.
Jason G Goldman, Justin N Wood. Anim Cogn 2015
6
1
16

Signal-driven computations in speech processing.
Marcela Peña, Luca L Bonatti, Marina Nespor, Jacques Mehler. Science 2002
189
1
16

The unrealized promise of infant statistical word-referent learning.
Linda B Smith, Sumarga H Suanda, Chen Yu. Trends Cogn Sci 2014
43
1
16

Unsupervised statistical learning in newly hatched chicks.
Chiara Santolin, Orsola Rosa-Salva, Giorgio Vallortigara, Lucia Regolin. Curr Biol 2016
14
1
16

Infants' statistical learning: 2- and 5-month-olds' segmentation of continuous visual sequences.
Lauren Krogh Slone, Scott P Johnson. J Exp Child Psychol 2015
17
1
16

Statistical learning across development: flexible yet constrained.
Lauren Krogh, Haley A Vlach, Scott P Johnson. Front Psychol 2013
56
1
16

Visual statistical learning in the newborn infant.
Hermann Bulf, Scott P Johnson, Eloisa Valenza. Cognition 2011
130
1
16

Measurement error and the replication crisis.
Eric Loken, Andrew Gelman. Science 2017
153
1
16

Constraints on Statistical Learning Across Species.
Chiara Santolin, Jenny R Saffran. Trends Cogn Sci 2018
43
1
16


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.

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