Notice bibliographique
Résumé
The untimely death brought to a stop the work on his Master of Science degree and a termination of a promising career in the conservation field. Drowned in the line of duty was Roger Schmitke on June 10, 1965, in the Redwater River near Edmonton, Alberta, Canada. Prior to his death, Roger had worked diligently on his research assignment and had collected all of the data deemed necessary for the completion of the thesis. Partial analysis of the data had been made. The present volume is an attempt to bring together his data and analyses for presentation to his graduate committee . It is understandably not in the form in which he meticulously would have presented it, but it does present the data on this important study. Many months of field research went into the project and additional time was spent in analysis of data. It was a pleasure to have been associated with Roger and his family during his academic career at Utah State University. His pleasing personality and professional approach to the problem of the class and field were always refreshing and stimulating. It is with regrets that we must present this work instead of having Roger do so himself. Wherever possible, the text was retained in the wording of Roger. Respectfully submitted,J. B. LowMajor Professor Abstract Annual productivity varied from 16.2 to 22.8 young per adult female based on placental scar counts. Summer juvenile mortality approximated 30 percent and annual mortality approximated 90 percent. Mortality of 90 percent each year resulted whether the population was trapped or not. Trapping took the place of other types of mortality. Adverse winter conditions were reflected in reduced muskrat body weights. Best quality furs were obtained in early winter - late October and November. Interspecific strife and food shortages appeared to be the most important mortality factors, although predation, movements, weather and parasites and diseases were known to have some adverse effect on the population. Most females produced two litters per season but some had three litters. Estimated density of 5.4 to 9.7 muskrats per acre was determined for the Big Island Lake marsh.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».