Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2024 Dataset
Bibliographic record
Abstract
The dataset is the public version of the CoRE MOF database updated in 2024 which includes 12,499 (out of 17,202) computation-ready and 13,125 (out of 23,635) not computation-ready MOF CIF files and precomputed material properties. The dataset includes structures reported up to early 2024. Precomputed properties: pore limiting diameter (PLD), largest cavity diameter (LCD), pore volume (PV), framework dimensions, accessible surface area, crystal density, topology, open metal site, MOFidv1, MOFidv2, DDEC06 partial atomic charges from PACMAN model, heat capacity, decomposition temperature, probability of solvent removal stability, probability of water stability, hydrophobic classification based on GEMC Dataset Directory Organization 1. CoREMOF2024DB_public.zip: dataset with computation-ready (CR) and not-computation ready (NCR) classifications CR dataset: 12,499 ASR (all solvent removed): 6,963 FSR (free solvent removed): 4,978 Ion (with ions): 710 NCR dataset: 13,125 Both Chen_Manz and mofchecker: 7,360 Chen_Manz: 1,565 mofchecker: 4,053 occupancy of a single atom is less than 1: 146 MOSAEC: 1 2. NCR_ASR_detail.xlsx, NCR_FSR_detail.xlsx, NCR_Ion_detail.xlsx: Details of NCR classification of all MOFs based on mofchecker and Chen_Manz method 3.ASR_data_20241125_internal.csv, FSR_data_20241125_internal.csv, ION_data_20241125_internal.csv: pore limiting diameter (PLD), largest cavity diameter (LCD), pore volume (PV), framework dimensions, accessible surface area, crystal density, topology, open metal site, MOFidv1, MOFidv2, DDEC06 partial atomic charges from PACMAN model, heat capacity, decomposition temperature, probability of solvent removal stability, probability of water stability, henry's coefficient classification of hydrophobicity, etc 4. unmodified4NCR.xlsx List of unmodified NCR structures (internal version) 5. mofid-v2.zip: XYZ files of linkers and metal nodes, errors (which is an "unknown" MOFid) 6. water.zip GEMC water isotherm data of CR dataset 7. TSA.zip Single isotherms of 35 MOFs used in TSA; TSA results and adsorption data at different feed conditions
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.100 | 0.087 |
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".