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
In his speech Professor Nishat discussed the international and national context of climate change issues on a different aspect and emphasized to accelerate adaptation process of Bangladesh to meet the climate change challenges.He stressed the need for more agricultural researches to invent climate-tolerant crop varieties to address the challenges of food crisis in near future because of climate change.Due to the climate change, food production will drastically fall in near future resulting severe food crisis across the globe as well as in the country.He urged those journalists who will cover the Cancun climate conference scheduled to start in Mexico on November 29 to know about the procedure of negotiation and disseminate objective information.He also mentioned due to climate change, saline water of the Bay of Bengal has already started to enter into the country's inland fresh water posing threat to bio-diversity of fishes, he mentioned.He shared to press people that the journalists who will go to cover the program in Cancun should aware about the different groups meeting, side-by side meetings, agenda and know the key negotiators of the Conference.Professor Nishat also meet question and answer session.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it