Bibliographic record
Abstract
Three experimental groups succeeded recently to close, at the same time, locality and fair sampling loopholes and confirmed that realism understood as counterfactual definiteness may not be used to explain quantum phenomena. Since there is now a general consensus that Bell inequalities are violated it is important to understand what does it mean and how can we explain the existence of strong correlations between outcomes of distant measurements, predicted by quantum mechanics. Do we have to announce that: Einstein was wrong, Nature is not local and the correlations are produced due to the quantum magic and emerge, somehow, from outside space-time? We reject such conclusions and we show that violations of various inequalities can neither prove completeness of quantum mechanics nor that Nature is not local. We propose simpler contextual explanation of long range correlations predicted by quantum mechanics which reconciles in some sense Bohr with Einstein and we conclude that there is no evidence that Nature plays dice. We argue that to prove predictable completeness of quantum mechanics one has to search for fine structures in experimental data which might have been averaged out in standard statistical analysis and which were not predicted by the theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.010 | 0.031 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".