Poleward shifts and ecological changes of Arctic and Subarctic zooplankton and fish in response to climate variability and global climate change
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
No abstracts are to be cited without prior reference to the author.Conveners: Hein Rune Skjoldal (Norway), Carin Ashijan (USA), Louis Forter (Canada).CM 2017/E:516. Inter-annual variability of Calanus finmarchicus, C. hyperboreus and Metrida longa in subarctic waters north of Iceland 1990-2016. Astthor Gislason, Kristinn GudmundssonCM 2017/E:425. Age, growth rate, and otolith growth of polar cod (Boreogadus saida) in two fjords of Svalbard, Kongsfjorden and Rijpfjorden. Dariusz P. Fey, Jan Marcin WęsławskiCM 2017/E:529. Determining thermal preferences and limits of fish and zooplankton species using trawl survey observations. M. Elisabeth Henderson, Janet A. NyeCM 2017/E:676. Re-visiting the drivers of capelin recruitment in Newfoundland since 1991. Hannah Murphy, Pierre Pepin, Dominique RobertCM 2017/E:628. Regional differences in Ocean Conditions and Groundfish Distributional Changes in the Gulf of Alaska. Lingbo Li, Anne Hollowed, Steve Barbeaux, Edward Cokelet, Wayne Palsson, Phyllis Stabeno, Qiong YangCM 2017/E:192. Deciphering the relationship between historical abundance fluctuations in the offshore Atlantic cod (Gadus morhua) stock aroundGreenland and the environment. Karl-Michael Werner, Hans-Joachim Rätz, Ismael Núñez-Riboni, Heino O. Fock<br>
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 | 0.005 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it