Notice bibliographique
Résumé
By Craig CaldwellTemperatures in Mar were below average, with the statewide mean, high, and low ranging between the 25th and 35th percentiles.Statewide, precipitation was a bit above average but varied considerably.The southern quarter of the state received 150 to 200% of its usual amount and the middle half between 90 and 200%, but the northwest and lakeshore received from less than half to about 90% of their norms.In Apr, the average, high, and low temperatures statewide were all in the upper third of the 121 years with data but did not break into the highest 20%.Precipitation was above average everywhere but the northwest corner, which received less than 90% of its norm.Rainfall in the rest of the state was up to double its usual amount except for the Portsmouth area, which was soaked with three to four times its average.May was among our hottest ever.The average temperature was our 11th highest, part of a heat wave which affected the entire northeast quadrant of the country and set many records in New England.The statewide average minimum and maximum followed suit; they were our 14th and ninth highest, respectively.Cleveland and Akron tied or set several record high temperatures between 07 and 09 May.The lower than average rainfall overall brought no relief.The southern half of the state received from less than 25% of its norm to only about 90%.Paradoxically, most of the northern half received between 90 and 150% of its average rainfall and small areas in the northeast and northwest were drenched with up to triple their usual amount.Weather data are from the National Weather Service (http://water.weather.gov/precip/),the National Oceanic and Atmospheric Administration (http://www.ncdc.noaa.gov/temp-and-precip/maps.php and http://www.ncdc.noaa.gov/extremes/records/), and the Plain Dealer.Andy Jones posed an interesting question: Are we seeing more American White Pelicans because they are more common than 20 years ago, or because there are more observers?He suspected the latter, which I agree is likely a part of the answer.However, we found that eBird data show larger numbers are wintering further north along the Atlantic coast than before, which could contribute to more pelicans crossing Ohio on the way to their nesting areas in the middle of the continent.Granted, eBird usage is also growing, so the "more observers" phenomenon may also
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 | 0,004 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,001 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,013 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,170 | 0,099 |
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 ».