Theme session B - Spatial management, climate change, and biodiversity
Bibliographic record
Abstract
ICES Annual Science Conference Book of abstracts for theme session B: Spatial management, climate change and biodiversity Conveners: Catarina Frazão Santos (Portugal), Andrew Kenny (UK), Tundi Agardy (USA) CM 11: Lyme Bay Offshore Mussel Farm – an OECM case study CM 29: Requirements and availability of prey for north-eastern pacific southern resident killer whales CM 35: Fine-scale oceanographic drivers of pelagic biomass around a tropical coral atoll within the Chagos Archipelago Marine Protected Area CM 40: Jointly modelling Atlantic bottlenose dolphin distributions and prey species: evidence of strong ties to drumming prey species and temperature CM 49: Can High-Seas Fisheries Closures Qualify as Other Effective Conservation Areas? CM 54: Deep-sea silver scabbardfish Lepidopus caudatus ecology, biology, and fisheries in the Azores CM 58: Developing a subseasonal forecasting tool to reduce fisheries bycatch in the Northeast US CM 96: Vulnerability Analysis of the Western Baltic Small-Scale Fishery CM 127: An ecological assessment to determine Vulnerability of the Portuguese Fisheries to climate change CM 128: Socio-economic vulnerability assessment of Portuguese fisheries to climate change CM 137: Retrospective forecasting of seasonal spatiotemporal dynamics to identify bycatch hotspots in the yellowtail flounder fishery on the Grand Banks CM 155: Exploration of life cycle spatial distribution and dependencies of the European hake in the Gulf of Lion, Western Mediterranean Sea CM 157: Other Effective Area-Based Conservation Measures and the North-East Atlantic Fisheries Commission - science needs CM 161: Consequences of model assumptions when projecting habitat suitability: a caution of forecasting uncertainties CM 167: Future projections of suitable habitat for vulnerable species and commercial fish around north western Europe CM 171: Taking urgent action to combat climate change and its impacts through marine Area-Based Management Tools CM 198: Improved transdisciplinary science for effective ecosystem-based maritime spatial planning and conservation in European Seas - MarinePlan CM 248: Spatial and temporal variability of meroplankton transport with Atlantic waters to the Arctic during present climate change CM 344: Ocean planning in polar regions: A way forward CM 438: Management for sustainable cephalopod fisheries in Europe: what are the options? CM 348: Distribution of demersal species and their hot spots of aggregation in the Adriatic Sea under climate change CM 367: Environmental effects on assemblages and biological characteristic of demersal community in the Flemish Cap CM 383: Global perceptions on the need for climate-smart marine spatial planning CM 385: Contrasting the VMS vs. AIS coverage on the fishery dynamics of the tropical tuna purse-seine fleet CM 394: Addressing long-term changes in Plankton using ‘pelagic’ and ‘food web’ indicators in the North-East Atlantic CM 396: A dominant effect of species richness on community biomass in a benthic ecosystem CM 409: Benthic community distribution pattern in a Southern Norwegian fjord-coastal system CM 422: Effects of climatic changes and alternative fisheries management measures in the Adriatic Sea CM 427: Climate change affects the distribution of diversity across marine food webs CM 428: Spatiotemporal trends of Chamelea gallina (Linnaeus, 1758) recruitment in the Adriatic Sea using a Bayesian hierarchical modelling approach CM 434: Distributional changes of marine fish in Irish waters CM 449: Evaluation and characterization of fish nursery habitats in French Guiana tropical coastal habitats CM 466: Blue management under a changing climate: Marine spatial planning and the social-ecological perspective CM 472: Size-structure, growth, and mortality rate of the deep-sea silver scabbardfish Lepidopus caudatus in the Azores CM 473: Spatial distribution of the silver scabbardfish Lepidopus caudatus in the Azores archipelago CM 482: Contributing to global marine biodiversity conservation goals with area-based fisheries management: A typology-based evaluation CM 497: Do the management units of Sebastes mentella in the North Atlantic comply with its biological units identified by genome-wide SNP data? CM 510: A systems approach to marine spatial planning CM 526: A two-fold spatiotemporal approach reveals cross-scale environmental drivers across metapopulation subunits CM 562: Evaluating the role of Geomorphology in Modelling Suitable Habitat for Adult Snow Crab (Chionoecetes opilio) in Atlantic Canada Under Future Ocean Climates CM 570: Combining multiple sources of evidence to quantify the spatial and temporal dynamics of seabird prey fish in the North Sea
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.244 | 0.067 |
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".