Theme Session F – Integration of molecular tools for biodiversity, risk assessment, ecosystem advice within a changing climate
Bibliographic record
Abstract
Book of abstracts of theme session F:Integration of molecular tools for biodiversity, risk assessment, ecosystem advice within a changing climateConveners: Dave Clarke (Ireland), Cynthia McKenzie (Canada), Rowena Stern (UK)CM 68: DNA metabarcoding of zooplankton species diversity and climate-driven range shifts based on time-series ecosystem monitoring of the NW Atlantic continental shelfCM 72: Detection of eDNA functional indicators using digital PCR (dPCR): Comparison with existing methods for biomonitoring environmental pressures in estuariesCM 115: Time Series and Network Theory application for benthic microbial community metagenomes: From Community structure to community functioningCM 126: DNA metabarcoding for large-scale studies and monitoring of fish trophic interactionsCM 158: Spatio-temporal dynamics of Arctic eukaryotic microbes from days to decades and across habitatsCM 163: Exploring biodiversity in an ecosystem impacted by seafloor plastics is made easier by eDNA metabarcodingCM 199: Exploring the potential for oyster aquaculture to remediate biodiversity loss in oyster reef habitats using non-destructive environmental DNA samplingCM 225: Seasonal variation of non-indigenous invertebrate species in recreational marinas in the north of Portugal using DNA metabarcoding: impact of sample typeCM 226: Estuarine microbenthos metabarcoding for ecosystem status assessment − the Basque coast and beyondCM 239: Evaluation of environmental DNA capture and extraction methods for Harmful Algal Blooms biomonitoringCM 250: Development and validation of molecular markers for early detection of Alexandrium spp. in the west coast of IrelandCM 266: Development and validation of a HT-qPCR screening panel for efficient high-resolution bioassessment of ecological and economically important shellfish species in Irish coastal watersCM 268: Detecting two marine non-indigenous species from the French coast using eDNA and molecular approachesCM 269: Differences between microbial communities and their ecological associations in clean and polluted estuaries from the Basque CountryCM 383: Improving assessment of diadromous fishes distribution in the North-East Atlantic using eDNA analysesCM 389: Plankton community response to climate-driven salinity change and warming: A mesocosm experiment comparing morphology‐based identification and metabarcodingCM 398: Genetics as a tool for sustainable fishing and protection of vulnerable marine ecosystems - VMECM 418: Monitoring the variability of microplankton communities’ structure in the Alboran Sea with high throughput sequencingCM 425: Coastal microbiomes in estuarine ecosystems of France: the eDNA network ROMECM 430: Integration of new methods for evaluating marine protected area connectivity and efficiencyCM 445: Characterization of VMEs with DNA: mind the gapCM 454: Trawl-associated opportunistic eDNA sampling probe for large scale fish community assessmentCM 532: A meta-analysis of potential biomarkers linked to the consumption of microplastics in marine fishCM 590: Comparison between COI metabarcoding and microscopy for zooplankton monitoring of the Adriatic biodiversityCM 644: Comparison of the three metabarcoding genes (18S, 28S and COI) for the Adriatic Sea zooplankton biodiversity monitoring
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.271 | 0.141 |
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".