Correction to Raising the value of research studies in psychological science by increasing the credibility of research reports
Bibliographic record
Abstract
This document provides corrections for the paper titled “Raising the value of research studies in psychological science by increasing the credibility of research reports: The Transparent Psi Project” (1). The corrections are in response to the protocol deviations uncovered by a new research audit conducted on this project by James E. Kennedy (2). The audit report lists a number of protocol deviations that were missing or were not explicitly listed as such in the original paper. As noted in the new audit report, these protocol deviations are unlikely to have significant influence on the study conclusions, especially given that the study obtained a null result. Nevertheless, if the study would have obtained a positive result (evidence supporting the ESP hypothesis), some of these protocol deviations would have potentially been more impactful casting doubt on such a controversial finding. In this document corrections are listed for all protocol deviations mentioned in this new audit report.
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.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Reporting · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.228 | 0.867 |
| Meta-epidemiology (narrow) | 0.004 | 0.008 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.023 | 0.025 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.030 | 0.010 |
| Open science | 0.014 | 0.015 |
| Research integrity | 0.027 | 0.038 |
| Insufficient payload (model declined to judge) | 0.120 | 0.103 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".