Primary productivity of planet earth: biological determinants and physical constraints in terrestrial and aquatic habitats
Bibliographic record
Abstract
C technique.Concepts of light interception and conversion ef®ciencies introduced.1980s Eddy covariance technique developed.High precision TCO 2 and O 2 determinations Underestimation of NPP from IBP methods allowed extension of in situ diel techniques to demonstrated.oligotrophic regions.Satellite remote sensing of leaf area and Satellite remote sensing of pigments introduced interception ef®ciency developed (NDVI).and bio-optical algorithms for obtaining Rhizotrons and computerized image analysis for productivity developed.estimating below-ground NPP.Questions about 14 C technique largely resolved.Effective models for scaling from the Emergence of coupled physical-biological modelling.photosynthetic process to canopies developed.Trace element clean techniques allow iron-Mass isotope analysis allows separation of C 4 and C 3 components.limitation to be demonstrated in bottles.HPLC technique for measuring phytoplankton pigments perfected.1990s Long-term eddy ¯ux networks developed.Fast Repetition Rate ¯uorescence technique Links to routine satellite monitoring of regional NDVI.introduced for in situ estimation of Chlorophyll ¯uorescence and absorption photosynthetic ef®ciency.spectroscopic methods for remote sensing of Iron limitation demonstrated unambiguously photosynthetic conversion ef®ciency attempted.during Lagrangian studies involving water mass labelling with SF 6 .Widespread application of analytical ¯ow cytometry to phytoplankton populations.2000+ Major breakthroughs needed:Major breakthroughs needed: Plant respiration models of the detail available for Remote sensing of photosynthetic ef®ciency photosynthesis together with resolution of the to complement remote sensing of pigments direct effects of rising CO 2 .and light attenuation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".