MétaCan
Menu
Back to cohort
Record W2901719899 · doi:10.1093/icesjms/fsy155

A graphic novel from the 4th International Symposium on the Effects of Climate Change on the World’s Oceans

2018· article· en· W2901719899 on OpenAlexaff
Jason S. Link, Bas Kohler, Roger B. Griffis, Margaret M Peg Brady, Shin‐ichi Ito, Véronique Garçon, Anne B. Hollowed, Manuel Barangé, Robin Brown, Wojciech Wawrzynski

Bibliographic record

VenueICES Journal of Marine Science · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsNorth Pacific Marine Science Organization
Fundersnot available
KeywordsNothingClimate changeTheme (computing)Set (abstract data type)NarrativeResilience (materials science)Psychological resilienceAction (physics)Environmental ethicsHistoryPolitical scienceComputer scienceOceanographyPsychologyEpistemologyWorld Wide WebArt

Abstract

fetched live from OpenAlex

The world’s oceans are changing in response to a changing climate, these changes have significant consequences, there is much at risk, and action is needed now to increase the resilience of ocean ecosystems and the people that depend on them. That was the message from the 4th International Symposium “Effects of Climate Change on the World’s Oceans”, held from 4 to 8 June 2018 in Washington, DC. The symposium gathered ∼650 people from over 50 countries to discuss not only how to advance our understanding and scientific knowledge, but also how to enact solutions based on that science to address challenges facing the world’s oceans. Two perceptions were explored at the symposium: that we just do not know enough to act, and that there is nothing but bad news. The reality is that while better understanding of the causes and consequences of climate-related changes in ocean ecosystems is always useful, we already know enough to act. There are also opportunities, positive outcomes, and cause for hope in considering and communicating those actions. A professional graphic artist attended the meeting, and produced a range of amazingly insightful and often poignant cartoons as an effective means to share lessons from the conference in real time. As an entree into the special theme set, a selection of the cartoons has been assembled here, providing a narrative of the meeting and offering areas for future consideration.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.242
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueICES Journal of Marine ScienceSame topicOcean Acidification Effects and ResponsesFrench-language works237,207