Publications by vboyce
expt 5
Note: one participant wasn’t getting a partner, so they opened up a new tab, fiddled with the id and played themselves. So we exclude the game with player id YSB8RYRgF2tQjym2e, which is game AQXAv4FKrZxBrTQgE Summary Each game has: 4 “spiked” BoS trials where one of the rewards is high (25-30) and the other is normal (3-7) ~16 normal BoS tr...
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vlm-tangram incremental first pass
Probability assigned to correct answer Using absolute length To deal with length variability, we truncate at 20 words and downfill for utterances shorter than that. Choosing a somewhat arbitrary set of word positions (1,5,10) to look at by expt differences. Could use improved vis to add the actual tangram images… Using fractional length Rstud...
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mlp best
Model Accuracy by round and condition does seem to go up over time Model accuracy by tangram look at that above chance accuracy for everything Accuracy as funct of number of words Confusion Matrix versus truth looks reasonable – confusing the two kneeling-ish ones with each other, the two less feature-y ones Comparison with all tg-matcher dec...
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kid-tangrams expt 2
Exclusions TODO Figure out what to do with the 3.8 year old, oops TODO figure out what’s up with game 80 where video cuts out? Accuracy Description length Speed Similarities Analyses [ ] Logistic model of accuracy: correct ~ trialNum + (trialNum|game) + (1|target) (prior normal(0,1) for beta and sd, lkj(1) for correlation) [ ] Linear model o...
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dialign flailing
Summary of what was done I took the 4p-rotate data (~20 games) and only the complete games of those and ran them through a pipeline to detect shared phrases. This included: lowercase everything, lemmatize, and filter stop words from a (modified) list run everything through dialign to detect linguistic units (“phrases”) that are repeated (withi...
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Altmann & Steedman Maze replication
Background Altmann and Steedman (1988) looks at reading times at the disambiguating words for either VP or NP attached with-phrases as a function of the context. Their items are in the appendix, and look like this: 2;setup;A mechanic walked up to a car carrying a monkey wrench. He thought he’d have to change a tyre. 2;1-context;On examining the c...
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payne2008_rescue
Replication of Sleep Preferentially Enhances Memory for Emotional Components of Scenes by Payne, Stickgold, Swanberg and Kensinger (2008, Psychological Science) Author Daniel Ogunbamowo (dogun@stanford.edu) Published July 31, 2024 Links to github repo, osf preregistration, and the original paper Based on the prior write-up, describe any diffe...
15784 sym Python (13558 sym/48 pcs) 8 img 2 tbl
rescue_craig2014
Table of contents Introduction Summary of prior replication attempt Methods Power Analysis Planned Sample Materials Procedure Controls Analysis Plan Differences from Original Study and 1st replication Methods Addendum (Post Data Collection) Results Data preparation Results of control measures Confirmatory analysis Exploratory analyses Discus...
15334 sym Python (14134 sym/48 pcs) 8 img
random_forest_vlm_tg
Model Accuracy By round & condition It increases over repNum, which is … interesting?! By tangram Above chance at everything! No longer hates the ice skater. Confusion Matrix Comparison with all tg-matcher Compare the random forest with human results ## [[1]] ## ## [[2]] ## [1] "Correlation between random forest model and human 0.525" Indi...
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model-human-comp1
All tg-matcher Compare the model results (on individual speaker description ?) with human results from the whole dialogue. ## [[1]] ## ## [[2]] ## [1] "Correlation between Control - augment model and human 0.525" ## [[1]] ## ## [[2]] ## [1] "Correlation between Control - parts - color model and human 0.281" ## [[1]] ## ## [[2]] ## [1] "Correl...
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