DOI: 10.5281/zenodo.15591436
title: Raw and Processed Experimental Data, Stan Models, Analysis Notebooks, Dockerfile and Protocols for Reproducing the Fifth-Force Study

description: This Zenodo dataset (“Semantic Interaction Physics: Data, Code and Protocols for ‘The Fifth Fundamental Interaction’ (Version 3.0)”) contains all raw and processed materials needed to reproduce and extend the experiments, analyses, and modeling described in the associated peer-reviewed manuscript “The Fifth Fundamental Interaction: A Self-Consistent ‘Semantic Field’ Hypothesis and Its Coupling to the Known Four Forces” (PSBigBig, 2025; DOI: 10.5281/zenodo.15591437).

 

Dataset contents include:

 

1. Data files:

   • real_sound_data.csv – Raw acoustic waveforms and spectral data for three plant species (Arabidopsis thaliana, Solanum lycopersicum, Oryza sativa).  

   • real_ATP_responses.csv – Time-series measurements of ATP concentration (luciferase assay) for each specimen and stimulus group.  

   • real_multi_species.csv – Aggregated dataset combining per-plant values of semantic energy S, membrane potential shifts, Ca²⁺ imaging results, thermal responses, and NMR/gravity readings.

 

2. Code files:

   • sentiment_analysis.py – Python script to compute valence and arousal scores from audio files using openSMILE features.  

   • acoustic_energy.R – R script to calculate weighted acoustic energy ∫P(f,t) w(f) df dt.  

   • model.stan – Hierarchical Bayesian regression model in Stan for estimating β₀,s, β₁,s, σₛ across species.  

   • analysis.ipynb – Jupyter Notebook orchestrating the entire analysis pipeline: data import, cleaning, Stan model fitting, posterior visualization, sensitivity plots.  

   • Dockerfile – Docker specification installing all dependencies (R, Python, Stan, openSMILE, FLIR SDK) for one-click reproducibility.

 

3. Protocol documents:

   • SOP.pdf – Detailed Standard Operating Procedures for acoustic stimulus calibration, membrane electrode setup, Ca²⁺ imaging, ATP assay, thermal imaging, NMR, and atomic gravimetry.  

   • noise_spectrum.pdf – Background noise spectrum (0–20 kHz) confirming isolation chamber conditions (< 30 dB).  

   • speaker_calibration.pdf – Calibration logs for Bruel & Kjaer 2250 speaker and Sennheiser MKH 8020 microphone.  

   • electrode_calibration.pdf – Calibration details for Axon Instruments Axon 700A amplifier and microelectrode insertion depth checks.

 

4. Analysis notebooks and figures:

   • bayesian_results.ipynb – Jupyter Notebook containing posterior predictive checks, prior sensitivity analysis, and Tornado plots for σ, κ_sem, γ, V_eff.  

   • power_analysis.R – R script performing power/sample-size estimation via pwr.t.test based on pilot data (n=15).  

   • lambda_constraints_loglog.pdf – Final log-log figure of λ_int upper limits vs. interaction range, including Eöt-Wash, LLR, Casimir-AFM, bouncing-neutron, and UCN constraints.  

   • gI_mI_scan.pdf – Parameter-space scan overlay of g_I vs. m_I limits from IAXO and CASPEr experiments.

 

5. LICENSE – CC-BY-4.0 license for data; MIT license for code.

 

6. README.md – Project overview, instructions for reproducing analysis, Docker usage, and links to Zenodo record and OSF preregistration.

 

Abstract (Dataset Description):

This dataset provides full transparency and reproducibility for the interdisciplinary study proposing a “semantic field” φ_sem as a candidate fifth fundamental interaction. It includes all raw experimental measurements from multi-species acoustic stimulation trials (N = 270 plants across three species), accompanying high-precision NMR and atomic gravimetry data, comprehensive scripts (Python & R) to compute semantic energy S, and the Stan code to perform hierarchical Bayesian inference. Detailed Standard Operating Procedures (SOPs), calibration logs, and sensitivity analyses are provided to guide independent replication. The dataset also features finalized constraint plots for λ_int vs. distance, as well as advanced parameter scans for the pseudo-scalar mediator φ_I coupling. All files are containerized via Docker for one-click reproducibility. This resource aims to catalyze cross-disciplinary engagement among physicists, biologists, and data scientists by enabling rigorous validation of language-driven forces in living systems.

 



Contact Information (English):





Name: PSBigBig




Affiliation: Independent Researcher / Developer




Email: hello@onestardao.com




Website: https://onestardao.com