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Upload VAD Paper 01 scripts, results, and computational artifacts (part 2)

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  1. 05-Research_Program-Affective_Provo/01-Fixation_Duration_Research/VAD-Paper_01-Interaction_Within_Affect/02-Results/05-LME-Effect-Plots/01-Conditional-Main-Effects/1-FFD/Val_x_Aro/Dominance/Dominance_metadata.json +57 -0
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+ ------
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+
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+
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+
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+ Conditioning
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1
+ Effect
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+ ------
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+ Arousal
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+
5
+ Effect Type
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+ -----------
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+ main_effect
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+
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+ Dependent Variable
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+ ------------------
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+ 1-FFD: First Fixation Duration
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+
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+ Model
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+ -----
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+ Val x Dom
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+
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+ Model Type
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+ ----------
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+ interaction
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+
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+ Predictor
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+ ---------
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+ Arousal
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+
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+ Moderator
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+ ---------
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+ None
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+
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+ Formula
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+ -------
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+ IA_FIRST_FIXATION_DURATION ~ Valence * Dominance + Arousal + Length + Predictability + Frequency
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+
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+ Prediction Method
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+ -----------------
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+ Fixed effects only
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+
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+ Confidence Interval
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+ -------------------
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+ 95% confidence interval for the estimated fixed-effect mean
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+
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+ Conditioning
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+ ------------
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+ All non-focal standardized lexical and affective predictors
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+ are held at z = 0.
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+
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+ Duration Scale
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+ --------------
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+ The LME dependent variable was modeled on the natural-log scale.
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+ Displayed millisecond values are exponentiated fitted values and
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+ are not lognormal bias-corrected arithmetic mean durations.
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+
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+ Percent-Change Reference
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+ ------------------------
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+ Model prediction with all standardized lexical and affective
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+ predictors held at z = 0.
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+
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+ Reproducibility
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+ ---------------
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+ The CSV prediction grid and JSON metadata are the primary
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+ machine-readable visualization records. PDF and SVG are durable
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+ vector outputs. The .fig.pkl file is provided for convenience
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+ but may depend on the Python/Matplotlib environment.
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+
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+ Generated
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+ ---------
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+ 2026-08-26T16:07:46
05-Research_Program-Affective_Provo/01-Fixation_Duration_Research/VAD-Paper_01-Interaction_Within_Affect/02-Results/05-LME-Effect-Plots/01-Conditional-Main-Effects/1-FFD/Val_x_Dom/Dominance/Dominance.fig.pkl ADDED
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+ "dependent_variable": "IA_FIRST_FIXATION_DURATION",
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+ "dependent_variable_label": "1-FFD: First Fixation Duration",
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+ "model": "Val x Dom",
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+ "effect": "Dominance",
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1
+ Effect
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+ ------
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+ Dominance
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+
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+ Effect Type
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+ main_effect
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+
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+ Dependent Variable
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+
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+ Model
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+
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+
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+ -----------------
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+ Fixed effects only
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+
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+ Confidence Interval
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+ -------------------
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+
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+ Conditioning
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+
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+ Duration Scale
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+
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1
+ Effect
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+ ------
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+ Valence
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+
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+ Effect Type
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+ -----------
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+ main_effect
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+
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+ Dependent Variable
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+ ------------------
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+ 1-FFD: First Fixation Duration
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+
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+ Model
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+ -----
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+ Valence
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+
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+ Model Type
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+ ----------
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+ main
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+
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+ Predictor
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+ ---------
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+ Valence
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+
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+ Moderator
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+ ---------
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+ None
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+
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+ Formula
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+ -------
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+ IA_FIRST_FIXATION_DURATION ~ Valence + Length + Predictability + Frequency
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+
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+ Prediction Method
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+ -----------------
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+ Fixed effects only
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+
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+ Confidence Interval
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+ -------------------
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+ 95% confidence interval for the estimated fixed-effect mean
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+
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+ Conditioning
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+ ------------
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+ All non-focal standardized lexical and affective predictors
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+ are held at z = 0.
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+
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+ Duration Scale
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+ --------------
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+ The LME dependent variable was modeled on the natural-log scale.
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+ Displayed millisecond values are exponentiated fitted values and
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+ are not lognormal bias-corrected arithmetic mean durations.
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+
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+ Percent-Change Reference
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+ ------------------------
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+ Model prediction with all standardized lexical and affective
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+ predictors held at z = 0.
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+
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+ Reproducibility
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+ ---------------
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+ The CSV prediction grid and JSON metadata are the primary
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+ machine-readable visualization records. PDF and SVG are durable
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+ vector outputs. The .fig.pkl file is provided for convenience
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+ but may depend on the Python/Matplotlib environment.
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+
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+ Generated
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+ ---------
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+ 2026-08-26T16:07:47
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1
+ Effect
2
+ ------
3
+ Arousal
4
+
5
+ Effect Type
6
+ -----------
7
+ main_effect
8
+
9
+ Dependent Variable
10
+ ------------------
11
+ 2-GD: Gaze Duration
12
+
13
+ Model
14
+ -----
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+ Aro + Dom
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+
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+ Model Type
18
+ ----------
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+ additive
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+
21
+ Predictor
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+ ---------
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+ Arousal
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+
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+ Moderator
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+ ---------
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+ None
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+
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+ Formula
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+ -------
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+ IA_FIRST_RUN_DWELL_TIME ~ Arousal + Dominance + Length + Predictability + Frequency
32
+
33
+ Prediction Method
34
+ -----------------
35
+ Fixed effects only
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+
37
+ Confidence Interval
38
+ -------------------
39
+ 95% confidence interval for the estimated fixed-effect mean
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+
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+ Conditioning
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+ ------------
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+ All non-focal standardized lexical and affective predictors
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+ are held at z = 0.
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+
46
+ Duration Scale
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+ --------------
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+ The LME dependent variable was modeled on the natural-log scale.
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+ Displayed millisecond values are exponentiated fitted values and
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+ are not lognormal bias-corrected arithmetic mean durations.
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+
52
+ Percent-Change Reference
53
+ ------------------------
54
+ Model prediction with all standardized lexical and affective
55
+ predictors held at z = 0.
56
+
57
+ Reproducibility
58
+ ---------------
59
+ The CSV prediction grid and JSON metadata are the primary
60
+ machine-readable visualization records. PDF and SVG are durable
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+ vector outputs. The .fig.pkl file is provided for convenience
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+ but may depend on the Python/Matplotlib environment.
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+
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+ Generated
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+ ---------
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+ 2026-08-26T16:07:47
05-Research_Program-Affective_Provo/01-Fixation_Duration_Research/VAD-Paper_01-Interaction_Within_Affect/02-Results/05-LME-Effect-Plots/01-Conditional-Main-Effects/2-GD/Aro_plus_Dom/Dominance/Dominance.fig.pkl ADDED
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+ {
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+ "dependent_variable": "IA_FIRST_RUN_DWELL_TIME",
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+ "dependent_variable_label": "2-GD: Gaze Duration",
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+ "model": "Aro + Dom",
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+ "model_type": "additive",
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+ "effect": "Dominance",
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+ "prediction_method": "Fixed effects only",
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+ "confidence_interval": 0.95,
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+ "confidence_interval_type": "Fixed-effect mean confidence interval",
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+ "duration_transformation": "Natural log",
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+ "back_transformation": "exp(log fitted value)",
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+ "percent_change_reference": "All standardized lexical and affective predictors held at z = 0",
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+ "y_axis": "percent",
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