Original data for publication: Enriched rearing environment enhances fitness-related traits of salmonid fishes facing multiple biological interactions
Bibliographic record
Abstract
The data file contains original data for two experiments described in the publication: Karvonen A., Klemme I., Räihä V., Hyvärinen P. 2023. Enriched rearing environment enhances fitness-related traits of salmonid fishes facing multiple biological interactions. Canadian Journal of Fisheries and Aquatic Sciences. doi 10.1139/cjfas-2023-0083. Authors and contact information: Anssi Karvonen, University of Jyväskylä, Finland, anssi.karvonen@jyu.fi Ines Klemme, University of Jyväskylä, Finland, ines.klemme@jyu.fi Ville Räihä, University of Jyväskylä, Finland Pekka Hyvärinen, Natural Resources Institute Finland (Luke), pekka.hyvarinen@luke.fi 1. Data file: experiment1.csv variables: fish_IDunique fish identifier for the passive integrated transponder of the experimental fish populationone of five fish populations of origin rearingone of two fish rearing treatments, either ‘standard’ or ‘enriched’ infectionone of two fish infection status, either uninfected (0) or infected (1) lengthbody length (mm), measured directly before stocking to experimental tanks cataractaverage percentage of cataract coverage across both eyes estimated directly before stocking to experimental tanks tankone of eight unique experimental tank identifiers for the experimental replicates predatorone of two predation treatments in the tanks, either predator absent (0) or predator present (1) ant_streambinary, detection of fish at the stream-side antenna in the tank, categorized as no detection (0) and detection (1) ant_poolbinary, detection of fish at the pool-side antenna in the tank, categorized as no detection (0) and detection (1), the latter indicating entry into the pool latency_entrylatency to the first entry into pool (hours since the start of the experiment) changesnumber of changes between the stream and the pool side of the experimental tank time_poolproportion of time spent in pool side of the tank throughout the experiment growthpercentage change in body length from the beginning until the end of the experiment survivalfish survival categorized as either not survived (0) or survived (1) 2. Data file: experiment2.csv variables: fish_IDunique fish identifier for the passive integrated transponder of the experimental fish populationone of five fish populations of origin rearingone of two fish rearing treatments, either ‘standard’ or ‘enriched’ infectionone of two fish infection status, either uninfected (0) or infected (1) lengthbody length (mm), measured before experiment 2 cataractaverage percentage of cataract coverage across both eyes tankone of four unique experimental tank identifiers for the experimental replicates timeone of two time points of recording measurements, March 2018 (1) and July 2018 (2) growthpercentage change in body length survivalfish survival categorized as either not survived (0) or survived (1)
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.504 | 0.149 |
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".