Data accompanying "Shotgun proteomics reveals physiological response to ocean acidification in Crassostrea gigas"
Bibliographic record
Abstract
These are the raw data that accompany Table 1, Figure 1, Figure 3, and Figure S2 in Timmins-Schiffman E, Coffey WD, Hua W, Nunn BL, Dickinson GH, Roberts SB. (2014) Shotgun proteomics reveals physiological response to ocean acidification in Crassostrea gigas. PeerJ PrePrints 2:e388v1http://dx.doi.org/10.7287/peerj.preprints.388v1. Table 1. Water chemistry summary data. Mean and ± standard deviation are provided for the 29 day experiment. Salinity is an average of nineteen measurements and AT was measured four times. pH and temperature values are from the continuous monitoring by the DuraFET probe. pH, temperature, salinity, and AT were directly measured and all other parameters were calculated using CO2calc (Robbins et al., 2010). Figure 1. Data for mean Vickers microhardness and fracture toughness of C. gigas shells. Hardness and fracture toughness values are proviced for each oyster from the low (400 µatm CO2), mid (1000 µatm) and high (2800 µatm) treatments. Figure 3. Oyster mortality over 6 days from heat shock exposure at 42, 43, and 44°C after incubation at 400, 800, 1000, or 2800 µatm CO2 for 1 month. Figure S2. Tissue mass (in mg) and glycogen content (µg/µl) for each oyster analyzed from low (400 µatm CO2), mid (800 µatm), and high (2800 µatm).
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 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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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; both teacher heads agree on what is shown here.
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".