Bibliographic record
Abstract
Introduction: macrophysiology During the early part of the twentieth century, comparative physiological studies were as much at home in ecological journals as they were in those devoted to physiology. Indeed, Shelford (1913) considered ecology to be a “branch of general physiology which deals with the organism as a whole…and which also considers the organism with particular reference to its usual environment”. For reasons that have been discussed elsewhere (e.g. Huey, 1991; Spicer and Gaston, 1999; Chown et al. , 2004) ecology and physiology subsequently parted ways with both increasing their focus on smaller-scale questions. Although large-scale ecological and biogeographic work continued, interest in physiological mechanisms waned (see e.g. Myers and Giller, 1988; Lomolino and Heaney, 2004). In much the same way, large-scale comparative physiological ecology dwindled in significance, making studies such as those by Scholander et al. (1953) and Brattstrom (1968) milestones along an increasingly deserted road. Clearly, investigations of animal responses to the environment continued (the work of Bartholomew stands out especially (Dawson, 2005) (see also reviews in Prosser, 1986; Angilletta et al. , 2002; Hoffmann et al. , 2003), and the development of methods to correct for phylogenetic non-independence prompted a resurgence of interest in understanding the evolution of physiological traits and their variation among species and higher taxa (Feder et al ., 2000). However, by the late 1980s, the subject of organismal physiological diversity was in several ways thought to be a dead end.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".