Personal characteristics, occupational stress and turnover intentions among school teachers in Negeri Sembilan, Malaysia
Bibliographic record
Abstract
Paclitaxel (PTX) is one of the three most widely used chemotherapeutic agents, together with doxorubicin and cisplatin, and is first or second line treatment for several types of cancers. In 2000, Taxol, the conventional formulation of PTX, became the best-selling cancer drug of all time with annual sales of 1.6 billion. In 2005, the introduction of the albumin-based formulation of PTX, known as Abraxane, ended Taxol's monopoly of the PTX market. Abraxane's ability to push the Taxol innovator and generic formulations aside attracted fierce competition amongst competitors worldwide to develop their own unique, new and improved formulation of PTX. At this time there are at least 18 companies focused on pre-clinical and/or clinical development of nano-formulations of PTX. These pharmaceutical companies are investing substantial capital to capture a share of the lucrative global PTX market. It is hoped that any formulation that dominates the market will result in tangible benefits to patients in terms of both survival and quality of life. Given all of this activity, here we address the question: Who is going to win the battle of "nano" paclitaxel?
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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".