Bibliographic record
Abstract
This upload contains predicted interactomes for 23 species derived from meta-analysis of co-fractionation mass spectrometry (CF-MS) data. The following individual organisms are represented: Arabidopsis thaliana Brassica oleracea Caenorhabditis elegans Chaetomium thermophilum Chlamydomonas reinhardtii Dictyostelium discoideum Drosophila melanogaster Glycine max Homo sapiens Mus musculus Nematostella vectensis Oryza sativa Plasmodium berghei Plasmodium falciparum Plasmodium knowlesi Saccharomyces cerevisiae Strongylocentrotus purpuratus Triticum aestivum Trypanosoma brucei Xenopus laevis Escherichia coli Anabaena sp. PCC 7120 Synechocystis sp. PCC 6803 Network inference was performed by training a random forest classifier on known complexes (from CORUM or EcoCyc, for eukaryotes and prokaryotes respectively) to predict interacting protein pairs in cross-validation. Files include the complete classifier scores for every possible protein pair, sorted in descending order. The resulting networks can then be thresholded at an arbitrary precision.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.076 | 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".