Bibliographic record
Abstract
Data were collected in summer 2022 at the Station de biologie des Laurentides de l’Université de Montréal (Saint-Hippolyte, Qc, CA). The experiments were carried out in the laboratory on wild caught pumpkinseed sunfish (Lepomis gibbosus). For each individual, data were recorded on time spent with infected and uninfected conspecifics, lake of origin, total and standard length, body mass, spleen mass, sex, number of cestodes, trematodes and other parasites (yellow grub, white grub, nematodes). The purposes of the data were to assess whether uninfected pumpkinseed sunfish display avoidance behaviour towards infected conspecifics, whether they can detect infection using chemical and/or visual cues and whether the expression of this behaviour is influenced by the level of parasite exposure of focal fish in their natural environment.For each fish (ID), 2 trials were done to measure the time spent with each type of conspecifics (infected and uninfected). We used visual and chemical cues separately.-Control 1: Unifected conspecifics VS No fish-Control 2: Infected conspecifics VS No fish-Treatment: Infected conspecifics VS Unifected conspecific
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.136 | 0.103 |
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".