Color Infrared Photography Is Not a Good Predictor of Macro Invertebrate Abundance on Mudflats Used by Shorebirds
Bibliographic record
Abstract
The applicability of color infrared photography to indirectly predict prey abundance for shorebirds was tested by measuring the chlorophyll concentrations of primary producers on the mudflat surface at eleven migratory stopover sites of shorebirds in Georgia Strait, British Columbia during southward migration in July and August 2002. Many shorebirds are associated with regions of high coastal zone productivity, which may contribute to high prey abundance. Chlorophyll levels of primary producers contribute to the red tones of an infrared photograph. The hue of an infrared photograph was positively related to the chlorophyll concentration of the sediment surface across all sites. However, invertebrate density was not strongly related to surficial sediment chlorophyll concentration or photograph hue. The color infrared photography method is useful to quickly assess the surficial sediment concentration of the phytobenthos, but of low value to estimate invertebrate prey densities.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".