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
Fish cell lines are relatively easy to culture and most have simple growth requirements that make cross contamination a potential problem. Cell line contamination is not an uncommon incident in laboratories handling more than one cell line and many reports have been made on cross contamination of mammalian cell lines. Although problems of misidentification and cross-contamination of fish cell lines have rarely been reported, these are issues of concern for cell culturists that can make scientific results and their reproducibility unreliable. Proper identification of cell lines is thus crucial and protocols for routine and rapid screening are preferred. Cytogenetic evaluation, DNA fingerprinting, microsatellite analysis and PCR methods have been published for inter-species identification of many cell lines, but discerning intra-species contamination has been challenging. More complex DNA fingerprinting and hybridization techniques coupled with isoenzyme analysis have been developed to discriminate intra-species contamination, however, these require complex and time consuming procedures to enable cell identification thus are difficult to apply for routine use. A simple proteomic approach has been made to identify several fish cell lines derived from tissues of the same or differing species. Protein expression signatures (PES) of the evaluated fish cell lines have been developed using 2-DE and image analysis. A higher degree of concordance was seen among cell lines derived from rainbow trout, than from other fish species. Similar concordance was seen in cells derived from the same tissues than from other tissues within the same species. These profiles have been saved in an electronic databank and could be made available to be used for discerning the origins of the various cell lines evaluated. This proteomic approach could thus serve as an additional, valuable and reliable technique for the identification of fish cell lines.
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 | 0.000 |
| 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) | 0.000 | 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 it