Fluid Level Measurement System in Oil Storage. Python, Lab-Based Scale
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Refineries, fuel depots, airports and storage terminals commonly use fluid level measurement in storage tanks. Different fluid level measurement techniques and devices differ in the inaccuracy of measurement results, costs, and company needs. In addition, these measurements seek reliability of measurement data, immediate response times, control in operations, oil movement, custody transfer and inventory control. The objective is to develop a computer system for measuring fluid levels in oil storage tanks, using ultrasonic and temperature sensors, creating a web application for an automated measurement system (SAM) for managing volumes of Petroleum. The study methodology is i) Analysis of measurement reports. ii) Selection of physical components of the computer system. iii) SAM algorithm design and web application, and iv) Validate the system. The SAM application developed in open source proposes functional modules for administration, control, security, management and monitoring of storage tanks, the status of physical components and generation of dynamic reports in real-time. The results show the control characteristics of storage tanks such as maximum and minimum volume, temperature, time, precise data records in less time than certain current computer structures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it