MEDIA RELATIONS - WHY WE NEED TO IMPROVE THE BIOTECH INDUSTRY'SRELATIONS WITH THE MEDIA
Bibliographic record
Abstract
At the first Biotechnology Industry Organization (BIO) meeting, in Toronto in 1994, the organisers had to hire a public relations firm to get members of the media to attend. In comparison, at last year's BIO 2001 meeting held in San Diego over 500 members of the press were registered and the organisers are expecting even greater media attention this year. In less than a decade the media has gone from being cynical, nervous or uninterested in biotechnology to embracing it. That is true, at least in the US, where there is a fledgling symbiotic relationship between the biotech industry and the business and science media.
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 | 0.021 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.028 | 0.043 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".