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.
Bibliographic record
Abstract
AbstractEarlier literature proposed a rank-based graphical tool called a chi-plot which, in conjunction with a traditional scatterplot of the raw data, can help detect the presence of association in a random sample from some continuous bivariate distribution. This article suggests an alternative display called a Kendall plot, or K-plot for short, which adapts the concept of probability plot to the detection of dependence. The new procedure, which is rooted in the probability integral transformation, retains the chi-plot's key property of invariance with respect to monotone transformations of the marginal distributions. K-plots are easier to interpret than chi-plots, however, because the curvature that they display in cases of association is related in a definite way to the copula characterizing the underlying dependence structure. In addition, K-plots have the advantage of being readily extendible to the multivariate context.KEY WORDS : Chi-plotCopulaKendall's tauNonparametric associationProbability integral transformationRankitsSpearman's rho
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it