Bibliographic record
Abstract
Summary 1 The replacement series has been used widely to assess interference, niche differentiation, resource utilization, and productivity in simple mixtures of species. Correctly used, the approach can lead to some valid interpretations. In order to avoid criticisms, however, researchers should appreciate the assumptions and limitations of this methodology. 2 A replacement series contains confounded species density treatments. Replacement series experiments therefore provide collective results and cannot distinguish separate contributions to interference by the constituents of a mixture. 3 In a replacement diagram, trends in observed yields per species can be due to a multitude of possible levels of intra‐ and interspecific interference. Similarly, trends in expected yields per species do not represent specific levels of intra‐ and interspecific interference. A replacement series is therefore unsuitable for the quantitative evaluation of interference or niche differentiation. 4 A standard replacement series, but not a proportional replacement series, may be used to detect an imbalance between intra‐ and interspecific interference for a component of a mixture. If competition for resources is assumed or known to be the sole cause of interference, then such experiments yield a qualitative evaluation of complementary resource utilization by the mixture components. 5 The possibility of total density dependence impedes generalization from a replacement series result. Other biases, due to initial size and time of observation, may occur with replacement series and related experimental structures. 6 Results from a replacement series are of questionable value in predicting the long‐term outcome of an association between species. 7 Replacement series are a valid setting, but not the only possible setting, for some kinds of yield comparisons. These include comparing productivity of monocultures with that of simple species mixtures. 8 In some cases, interpretations obtained from replacement series have not been confirmed using other methods but, on the whole, conclusions from replacement series do not seem to be characteristically different from those obtained using other approaches.
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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 | 0.014 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.150 | 0.086 |
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".