Оценка точности расчета ледовитости Охотского и Японского морей по данным дистанционного зондирования Земли и авиационных наблюдений
Bibliographic record
Abstract
The development of the Sakhalin Shelf is complicated by the influence of various weather factors. The information on the ice situation (the aquatorium ice coverage) is the most important of them. Information source is the data of the remote sensing whose role has essentially increased with the reduction of the on-land network of hydrometeorological stations and amount of aviation observation. For the analysis of this information various technologies of processing of long-term numbers of satellite, aerovisual and land observation are used, allowing to reveal features of dynamics of the considered parameter in the territory. First of all, it is possible to develop the technology of operative analysis to decipher space images. Decoding of pictures represents one of the most important and difficult processes of creation of thematic maps which are the basic means of organisation and interpretation of the data of remote sensing. This process provides data representation in a uniform cartographic projection, allows to combine the data received in various spectral ranges (space images of artificial satellite Meteor-3M, TERRA, AQUA, NOAA, ERS-2, Envisat, IRS, QuikSCAT and TOPEX/Poseidon and others). Sine 1970 to locate the edges of an ice file and borders of zones of various unity Japanese researchers use the technique of data handling of the radar-tracking sensing, based on the pattern recognition principle. The received results in the form of maps-schemes (with shading for black-and-white images or colour scale zones of various unity of ice) with frequency from twice a week to twice a month are exposed by the National centres of processing of hydrometeorological information of Japan (Japan Meteorological Agency) and the USA (National/Naval Ice Center) on the Internet. The data has been included in the initial number with the monthly step-type behaviour, calculated as an average arithmetic by results of all shootings executed in the second decade of each calendar month of the ice season only. The present paper deals with the precision estimation of computations for the sea ice extent of the Okhotsk and Japan seas with the use of the joint data of the Earth remote sensing and aero-visual observations for 1970-1991 winter seasons. The analysis has revealed that the mean difference in the data on the Japan Sea obtained with the use of these two observational methods during the 1970-1991 span makes up 12.4 thousand km 2 (11.6 % of the total area), and this difference for the Okhotsk Sea is 121 thousand km (8% of the total area). The correlation analysis of the remote sensing and aerovisual series of the ice data in the Japan and Okhotsk seas demonstrated that the Japan Sea data series are of moderate correlation; the correlation coefficient changed in the range from 0.16 (December) to 0.39 (January). The Okhotsk Sea data series are correlated to a greater extent: the correlation coefficient changed in the range from 0.72 to 0.96.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".