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This replication package is for the paper "Social Learning in Agriculture: A scalable Farmer-to-Farmer Extension Approach for Dairy Farmers" by Luc Behaghel, Jeremie Gignoux and Karen Macours (Paris School of Economics & INRAE)

The Supplementary Material provides the complete list of the Alopecia Areata Relapse Study Group members and affiliations, together with extended methodological details, additional results, statistical analyses, discussion, and study limitations supporting the findings reported in the main manuscript.

Table S1 Biomass, Mg concentration, and Mg isotopic compositions in rice and maize; Table S2 Mg mass of each organ as a percentage of the overall plant Mg mass; Table S3 Mg isotope fractionation between different samples (‰).

HPLC Chromatograms

This dataset contains all data for the associated manuscript, organized by figures. The data includes: Raw data for XRD, FTIR, and Raman spectroscopy. Raw measurements of sample mass and thickness used for calculating the shrinkage rate and density. Original electrical signal data captured during the sensing processes. Plot data for thermopower and raw capacitance measurements.

this is part of the Data and code for CHF

Datasets and R code for McCarthy RC, Haque S. 2026. Endocranial volume estimates for Sts 25 (Australopithecus cf. africanus). Nature & Anthropology. * Appendix Table A1 ('Appendix_Table_A1.xlsx'): Complete dataset of chimpanzee and hominin specimens including 'Min' and 'Max' measurement values [.xlsx file]; * Code S1 ('sts25_poly_regress.R'): R code used to generate single-variable (SV) and multivariate (MV) polynomial regression equations to predict EV for Sts 25 and 10 fragmentary hominin specimens [.R file]; * Appendix Table A2 ('Appendix_Table_A2.xlsx'): Results from single-variable (SV) and multivariate (MV) polynomial regression, including logged regression coefficients and statistics, correction factors accounting for log detransformation bias, standard errors of the estimate (SEE), multiple r2, and adjusted r2 [.xlsx file]; * Dataset S2 ('Sts25_forest.csv'): Used to make Figure 2. Variables: Variable, n, Pred [point estimate], SE, SD, LB [lower bound], Point [=Pred], UB [upper bound], for 12 single-variable (SV) regressions, 4 multivariate (MV) regressions, means +/- 95% CIs, 95% PIs for SV and MV models [.csv file]; * Code S2 ('Sts25_Fig2_forest.R'): R code used to make Figure 2 forest plot using the 'Sts25_forest.csv' dataset [.R file]; * Dataset S3 ('Sts25_ridgeline.csv'): Used to make Figure 3. Variables: Specimen (chimpanzees, hominins), Group (CHI=chimp; OHM=other hominin), Variable (B-Lc, B-La, B-Pc, B-Pa, B-Lc, B-La), Measurement [in mm]. Dataset is in 'long' format [.csv file]; * Code S3 ('Sts25_Fig3_ridgeline.R'): R code used to make Figure 3 ridgeline plot using the 'Sts25_ridgeline.csv' dataset [.R file]; * Dataset S4 ('Sts25_boxplot.csv'): Used to make Figure 4. Variables: Specimen [10 fragmentary hominins], ECV [in cm3], Equation [for 12 different models], Prediction [New, Old][.csv file]; * Code S4 ('Sts25_Fig4_boxplots.R'): R code used to make Figure 4 box plots using the 'Sts25_boxplot.csv' dataset [.R file]; * Dataset S5 ('africanus_dot.csv'): Used to make Figure 5. Variables: Specimen [12 A. africanus], Value [EV best estimates, cm3], Previous [Old, This study], Reference [untitled variable][.csv file]; * Dataset S6 ('sts25_hom_dot.csv'): Used to make Figure 5. Historical EV values and additional point estimates for A. africanus specimens. Variables: Specimen [Sts 19, Sts 25, Sts 58, MLD 1, StW 505], Value [EV in cm3], Previous [Older, This study2][.csv file]; * Code S5 ('Sts25_Fig5_dotplot.R'): R code used to make Figure 5 dot plot using the 'africanus_dot.csv' and 'sts25_hom_dot.csv' datasets [.R file]

This dataset contains raw data from a 2 × 6 between‑subjects online experiment conducted in April 2026. Participants were 635 Chinese adults recruited from the Wenjuanxing online panel. The experimental design manipulated two factors: AI risk visibility (visible vs. invisible) and information source (AI, scientists, governments, AI companies, traditional media, or science key opinion leaders). The data include pre‑test and post‑test measures of trust in AI and trust in science, as well as measures of perceived information credibility, fear of AI, AI usage frequency, social media use, perceived relevance, and demographic variables. The dataset is provided in CSV format and includes a codebook with variable labels and value descriptions. It supports replication of the main analyses reported in the manuscript, including ANOVA, mediation, moderated mediation, and three‑way interaction models.

Database relative to research on firefighters. The file comprises all data concerning the variables measured across three exercise protocols (0 kg, 11 kg, and 20 kg, pre- and post-test), such as heart rate, VO2 uptake, lactate, and the Stroop test. Additionally, baseline characteristics of the participants are included.

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