Bibliographic record
Abstract
The first attempts at culturing animal cells in vitro made use of biological fluids, such as serum or tissue extracts. It was in the 1950s that a scientific approach was adopted to determine the defined nutrients required for mammalian cell growth. The idea of a chemically defined media was pioneered by Eagle, who determined the minimum ingredients that were essential for the growth of a number of human cell lines. This led to the development of Eagle’s minimal essential media that consisted of 13 amino acids, 8 vitamins and 6 ionic species [1]. This formulation appeared to provide the requirements for the growth of a number of isolated cell lines if supplemented with animal-sourced serum. Higher cell densities were obtainable by increasing the component concentrations of Eagle’s minimal essential media and became established through basal formulations such as Dulbecco’s modification of Eagles medium (DMEM). Clonal cell growth of selected cell lines was obtained by enrichment with an enhanced range of nutritional components, largely through the early work of Ham to produce the well-known Ham’s F-12 medium, Sato had the ingenious idea of combining these two approaches to blend a basal media formulation – DMEM/F-12 – that has become widely used for the growth of multiple cell lines to high density [2]. However, despite the inclusion of up to 70 components in these well-defined basal media formulations, supplementation with dialyzed serum (~10%) is necessary to provide sustained growth of most 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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.020 |
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".