Challenges In Creating An American Kestrel Body Condition Index Based On Size-Adjusted Mass
Bibliographic record
Abstract
Size-adjusted mass is a common body condition index (BCI) used to indicate nonstructural energy reserves (fat and protein). BCIs are calculated from ratios of mass divided by a morphometric(s) or residuals of a regression between mass and a morphometric(s). The morphometrics used in BCIs must accurately represent structural size to reliably index energy reserves and, ideally, BCIs should be validated with comparisons to true fat and protein reserves. Many studies of American Kestrels (Falco sparverius) have included BCIs in ecological analyses; unfortunately, few studies have reported how well morphometrics represented structural size or provided validation of BCIs relative to independent measures of energy reserves. We evaluated relationships between several morphometrics and mass to better understand which morphometrics may best represent structural size for two kestrel populations: captive birds at McGill University in Montreal, Canada, and free-living kestrels in southwestern Idaho, U.S.A. We also compared BCIs based on different morphometrics with subjective (visual) fat scores. Our data showed few strong (r > 0.5) correlations between morphometrics and few strong correlations between each morphometric and mass. Moreover, correlations between morphometrics and mass depended on sex and location. Similarly, not all BCIs had statistically significant, positive correlations with subjective fat scores and correlations varied between sexes, suggesting that the reliability of each BCI differed between males and females. The morphometrics that best represent structural size most likely differ between males and females, and information from both sexes should not be combined to create one size measure for kestrels. Unless BCIs for specific American Kestrel subpopulations are validated, mass and additional qualitative information, such as fat scores, may be the most appropriate indicators of fat and protein stores.La masa ajustada por tamaño es un índice de condición corporal (ICC) usado comúnmente para indicar reservas de energía no estructurales (grasa y proteínas). Los ICCs son calculados a partir del cociente entre masa y una (o varias) medida/s morfométrica/s o los residuos de una regresión entre masa y una (o varias) medida/s morfométrica/s. Las medidas morfométricas usadas en ICC deben representar con precisión el tamaño estructural para indexar de modo fiable las reservas de energía e, idealmente, los ICCs deberían ser validados mediante comparaciones con reservas verdaderas de grasa y proteínas. Muchos estudios de Falco sparverius han incluido ICCs en los análisis ecológicos; desafortunadamente, pocos estudios han informado que tan bien las medidas morfométricas representaron el tamaño estructural y han brindado validación de los ICCs con relación a medidas independientes de reservas energéticas. Evaluamos las relaciones entre varias medidas morfométricas y la masa para entender mejor cuáles medidas morfométricas representan mejor el tamaño estructural en dos poblaciones de F. sparverius: aves cautivas en McGill University en Montreal, Canadá, y aves libres en el sudoeste de Idaho, U.S.A. También comparamos los ICCs basados en diferentes medidas morfométricas con puntuaciones subjetivas (visual) de grasa. Nuestros datos mostraron pocas correlaciones fuertes (r > 0.5) entre las medidas morfométricas y pocas correlaciones fuertes entre cada medida morfométrica y la masa. Más aún, las correlaciones entre medidas morfométricas y masa dependieron del sexo y el lugar. De modo similar, no todos los ICCs presentaron correlaciones positivas estadísticamente significativas con las puntuaciones subjetivas de grasa y las correlaciones variaron entre los sexos, sugiriendo que la fiabilidad de cada ICC varió entre machos y hembras. Las medidas morfométricas que mejor representaron el tamaño estructural variaron con mayor probabilidad entre machos y hembras, por lo que la información de ambos sexos no debe ser combinada para crear una med
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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".