Bibliographic record
Abstract
Authorship is very personal; when acknowledged, it is a source of pride of accomplishment. When denied, it feels like an affront. It has been years but I still remember writing the first few drafts of a paper which I shared but when it was later published in a different form by my colleague, my name was not on it. That’s the aspect of ownership cherished by authors. The reciprocal aspect from the reader’s perspective is accountability. Each and every author listed is responsible for the accuracy and integrity of the work as a whole. Any of the authors should be able to stand by the work and be able to investigate and resolve questions of ethics, duplicate submission, errors, libel, misconduct, fraud, plagiarism, bias, financial relationships, prior publication and the like. If one’s defence to such an allegation is ‘I just did the (hypothesis/literature review/illustration/data acquisition/analysis…) but had nothing to do with X’, you are not really an author of the work (although you should be acknowledged for your contribution). Those linked concepts of attribution, ownership and responsibility inform us at the CJRM when we interpret the ICMJE rules for authorship:1 ‘Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND Drafting the work or reviewing it critically for important intellectual content; AND Final approval of the version to be published; AND Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved’. In the end, was I really an author of the paper that lacked my name? No, the paper had gone through several transmutations, with which I was sympathetic, but I did not review, or in the end approve, the final form. I was an important contributor, but not an author.
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
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 | 0.001 | 0.000 |
| 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) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".