Bibliographic record
Abstract
The Earth’s gravity field is constantly changing due to mass redistribution from\nice melting in the cryosphere and geophysical processes. With use of data from\ndedicated gravity satellite missions variations in the Earth’s gravity field over a\ntime series can be determined.\nThis thesis tries to give an explanation on how the Earth’s gravity field changes on\na global scale and regionally with the use of data from the GRACE-mission over a\ntime period. With comparison between three different GRACE-solutions and the\nuse of SLR-observations, the mass changes over Greenland has been estimated. In\naddition, a further look into the lower degree spherical harmonics has been studied,\nto explain and give a conclusion of how the lower degree spherical harmonics from\nGRACE are affecting the calculations of the gravity field.\nGRACE-data has its uncertainties in the lower degree spherical harmonics. The\nC 20 -coefficients from GRACE has large variances and therefore needs to be replaced\nby SLR-values when looking at global variations. Trend calculations shows how\npost glacial rebound(GIA) influence Canada and Fennoscandia, and ice melting\nover Greenland, Alaska and Antarctica.\nThe investigation of lower degree spherical harmonic coefficients shows that it is not\nsignificant how the C 20 -coefficients are processed when estimating mass changes\nover the area of Greenland.\nDue to restricted spatial resolution of the gravity field models and spatial averag-\ning, it is hard to get a real estimate of the mass changes over a specific area. This\nis called the leakage effect and has been studied over the area of Greenland. The\nleakage effect has been estimated and restored, and mass change over Greenland\nhas been estimated to be between -1832.76 km^3 and -2087.72 km^3 , depending on\nthe model used.\n\n\nJordas tyngdefelt er i stadig endring på grunn av masseforflytning fra isavsmelting i kryosfæren og geofysiske prosesser. Ved bruk av data fra gravimetrisatelliter kan \ndisse variasjonene i jordas tyngdefelt bestemmes over en tidsserie.\n\nDenne oppgaven prøver å gi en forklaring på hvordan jordas tyngdefelt forandres globalt og regionalt ved bruk av data fra GRACE over en tidsperiode. Ved å sammenligne tre ulike GRACE-løsninger og ved bruk av SLR-observasjoner, har masseendringer over Grønnland blitt estimert. I tillegg har det blitt sett nærmere på de laveregrads sfærisk harmoniske koeffisientene, for å gi en forklaring på hvordan disse koeffisientene fra GRACE påvirker beregninger av jordens tyngdefelt.\n\nGRACE-data har sin usikkerhet i de laveregrads sfærisk harmoniske koeffisienter. C20-koeffisientene fra GRACE har store varianser og må derfor bli byttet ut med SLR-verdier når man ser på globale variasjoner. Trendberegninger viser hvordan postglasial landheving(GIA) påvirker områdene Canada og Fennoskandia, og i tillegg issmelting over Grønnland, Alaska og Antarktis.\n\nVed å se nærmere på de laveregradskoeffisientene kan det bli observert at det ikke er av stor betydning hvordan man behandler C20-koeffisienter når masseendringer over Grønnland blir estimert.\n\nPå grunn av begrenset romlig oppløsning og romlig glatting av tyngdefeltsmodeller, er det vanskelig å gi et realistisk estimat av masseendringer over et område. Dette blir kalt "leakage"-effekt. "Leakage"-effekten har blitt estimert og gjennopprettet, og masseendringer over Grønnland har blitt beregnet til å være mellom -1832.76 km^3 og -2087.72 km^3, avhengig av hvilken modell som har blitt brukt.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".