Monitoring and modeling studies of Cl<sup>–</sup>concentration in an atmospheric corrosion environment: An application to the no. 6 naphtha cracking complex
Bibliographic record
Abstract
The No. 6 Naphtha Cracking Complex was built on man‐made new land, which was itself filled by dredging sand from the sea. The local atmospheric environment is high in sodium chloride and humidity. Therefore, it is important to investigate and document background information about the atmospheric corrosion environment in the complex. From the results of only four sites of sampling and analyzing, the Cl– concentrations in the air, in fall and winter, were higher than those in spring and summer; and the Cl– concentrations in the air decreased from the upwind coastal zones to the downwind hinterland regions. In order to save the great expense of sampling and analyzing, a model was developed and utilized to predict the Cl– concentrations in the air at different locations and times. The regression analysis of the Cl– concentrations in air between actual measurement and prediction indicated a good fit. Therefore, the model may be applied to other, similar, corrosion environments and the predicted results can be used as references for future prevention strategies about atmospheric corrosion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".