Specific heat data in GaAs/AlGaAs at 5/2 filling fraction: 20200831 data set
Bibliographic record
Abstract
Each data set name incorporates the date in which the data was acquired. There are a total of 6 data sets as shown in the table below (the current one, 20200831, is part of it). In each data set there is a series of txt files (current one has 30) that contain relevant information about the dataset such as the magnetic field (both relative B* and absolute values), the FQH state as well as a table with the raw data file names and the corresponding quantities of interest (input square wave DC offset + amplitude in Volts, set temperature in Kelvin, mean/uncertainty of/in temperature in Kelvin, signal samples - averaging, resistor values in Ohms, gain, frequency in Hertz, time stamp and time difference between each acquisition in seconds). The name of these information files is composed of the date in which the data set was acquired, the cooldown number, the sample name/number and the conductance (G) followed by the file number (increment of 1). Furthermore, each data set contains all the raw data save in txt files (current one has 570). The name of each file begins with Zurich (ZH) is followed be the cooldown number, the date in which the dataset was acquired, the row number of the data matrix (for each new thermal bath - dilution refrigerator temperature) and the column number of the data matrix (for each different input voltage - i.e. square wave DC offset + amplitude at the same thermal bath - dilution refrigerator temperature). Each raw data file contains 2 columns. The first column is the time in seconds. The second column is the voltage drop across the sensing 1 kilo Ohm resistor in Volts (which translates to current across the Corbino device). This is the raw response (to the bipolar square wave input) of the 2D electron gas (2DEG) measured by the Zurich digitizer. Raw data to download: ZH-20C1-0831-1-00000.txt up to ZH-20C1-0831-30-00018.txt (570 files in total).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.020 |
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".