Permeability-Depth (KZ) Database by Ranjram, Gleeson, and Luijendijk (2015)
Bibliographic record
Abstract
/\/\/\/\ A Modest Permeability-Depth Database /\/\/\/\ Assembled by Mark Ranjram, MSc Candidate, McGill University, 2014. contact: mark.ranjram@mail.mcgill.ca Reference: Ranjram M, Gleeson T & Luijendijk E (2015) Is the permeability of crystalline rock in the shallow crust related to depth, lithology or tectonic setting? Geofluids, 15,106-119. -------------------------------------------------------------------- The database is provided in its entirety in the excel file "Ranjram_Gleeson_Luijendijk_KZ_Database.xls" The cleanest representation of the data is provided in the sheet labelled "Main Database." -------------------------------------------------------------------- The excel file is composed of five Sheets: 1. "Table of Contents" This sheet provides a brief description of each sheet. 2. "Data Grab" This sheet presents the raw data which makes up the database. The information here is roughly presented and should only be used if the user thinks there is an error in the main database (Although contacting the author is probably the best first step to take if an error is apparent). 3. "Methods" This sheet provides a qualitative description of the data assembled from each reference in the main database. A Y/N indicator is provided for each reference describing whether the data are included in the main database (Volcanic rocks are excluded from the main database). Individual depth-permeability data are listed for references which provide a compilation of permeability-depth values. An 'x' under Salinity and Temperature indicates that the reference provides measurements of Hydraulic Conductivity but has no indication of tempearture or salinity with depth. Salinity-depth and temperature-depth relationships for these data are inferred from salinity-depth and temperature-depth relationships provided by studies in similar or nearby regions. Where possible, a "root reference" is provided if the referenced study collected its permeability data from another study. 4. "Main Database" This sheet provides the cleanest presentation of the assembled data and is the main sheet in this file. This sheet indicates the Location, reference, rock type, depth, and permeability information for every point included in our study. All conductivity values are converted to permeability in units of m² and each conversion is described in the sheet. The columns labelled "RESULTS/WORKING VALUES" provide the information analyzed and considered in our study. "k error" describes the range of uncertainty in permeability centred at the "working value" of permeability. "depth error" provides the depth range over which the permeability measurement is taken, with the range centred at the value in the "Depth" column. The "BOUNDED DEPTH DATA" columns explicitly indicate the upper and lower depths at which the corresponding permeability measurement was made. 5. "Jump Off Sheet" This sheet lists the data in the Main Database into sortable columns of Location, Reference, Lithology, permeability-depth values, and maximum depth. This sheet is useful for sorting and extracting desired permeability values. The columns filled in green are the "RESULTS/WORKING VALUES" described in the "Main Database" sheet. The Max Depth column indicates the deepest depth associated with each point, and our study excluded points deeper than 2.5 km.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.150 | 0.098 |
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".