Facilitating translation in biotech entrepreneurship: evaluating novel training programs in commercialization for scientist-entrepreneurs
Bibliographic record
Abstract
The present research aims to assess the influence of green innovative behavior, technological capabilities, and university support on bio-entrepreneurship development in the Canadian context. The study also considered the bio-entrepreneurship training of students as mediators. Through the disbursement of questionnaire, the researcher collected data from the target audience. 246 questionnaires were analyzed through SPSS and AMOS. Results depicted those technological skills and green innovative behavior significantly influences BET, whereas the other direct associations have been resulted to be insignificant. But the mediation of bio-entrepreneurship training has been found to be insignificant among all hypothesized mediation associations. The present research holds various theoretical and practical implications. The research extends the growing body of literature regarding bio-entrepreneurship education on skill development in Canada. Practically, the study holds valuable implications for various stakeholders to boast skill development through bio-entrepreneurial education. The research limitations and future research indications have also been addressed in the study.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".