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Record W2970718617 · doi:10.4236/ojbiphy.2019.94018

Seed Germination and Their Photon Emission Profile Following Exposure to a Rotating Magnetic Field

2019· article· en· W2970718617 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Journal of Biophysics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsLaurentian University
Fundersnot available
KeywordsGerminationSunflowerMagnetic fieldRotating magnetic fieldPhotonHelianthusHorticultureBiologyEnvironmental scienceAgronomyPhysicsOptics

Abstract

fetched live from OpenAlex

A multitude of experiments have applied magnetic fields to plants or seeds and found a variety of different and sometimes contradicting results. A magnetic field generating device called the Chrysalis resonator has been shown to influence the brain activity of human participants, the photon emissions from bacteria, mammalian cell cultures and water. In this experiment sunflower seeds (Helianthus annus) were allowed to begin germination and then exposed to either the field generated by the Chrysalis resonator or a sham condition. Their growth and photon emissions were taken over the next 5 days. It was found that the seeds showed less germination 48 hours after exposure and significantly higher photon emissions when 3 seeds were measured together in a dish, but not if 2 seeds or 1 seed were measured. There were no significant differences in the photon measurements from the water the seeds were germinating in. These results may indicate that the seeds became more sensitive to the presence of neighbouring seeds. The photon emissions results were also significantly impacted by external weather conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.237
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it