Skip to main content
skillsmp

Menu

Scientifiques en sciences animales

Sciences de la vie, physiques et sociales · Compétences professionnelles · SOC 19-1011 · 142 skills

Contexte du métier

Ces tâches O*NET décrivent le métier et donnent le contexte de la correspondance SOC ; elles ne signifient pas que chaque Skill de la liste accomplit toutes les tâches.

  • Study nutritional requirements of animals and nutritive values of animal feed materials.
  • Write up or orally communicate research findings to the scientific community, producers, and the public.
  • Develop improved practices in feeding, housing, sanitation, or parasite and disease control of animals.

Les tâches O*NET sont affichées dans leur langue source (anglais). Les données sur les tâches sont extraites de la O*NET® 29.1 Database de l’USDOL/ETA et utilisées sous CC BY 4.0.

Sources représentatives

Un échantillon limité de Skills populaires associés à ce métier, avec au plus un Skill par dépôt GitHub. La liste complète suit ci-dessous.

broiler-feed-intake-calculator-and-formulator
553
ECNU-ICALKECNU-ICALK/AutoSkill
Calculates daily feed intake for broiler chickens from day 1 to 32 based on a multi-phase recipe and target weight, and identifies or adds missing nutritional supplements like calcium, phosphorus, and vitamins.
withdrawal-times
30
OpenVet-ProjectsOpenVet-Projects/VetClaw
Food animal drug withdrawal time lookup for meat, milk, and egg residue avoidance. References FARAD (Food Animal Residue Avoidance Databank) and FDA-approved label withdrawal periods.
journal-intelligence
28
eniktabeniktab/scientific-paper-writer
Fetch live submission requirements for any scientific journal before writing. Use before scientific-writing or any manuscript task: retrieves author guidelines, word limits, abstract format, figure limits, citation style, AI authorship policy (exact disclosure language), and LaTeX template via WebSearch/WebFetch. Stores results in journal_profile.yaml as the single source of truth for all formatting decisions. Covers Nature family, Cell Press, Elsevier, Wiley, Springer, PLOS, PNAS, ACS, RSC, IEEE, ACM, and any other journal.
agri-deep-research
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Deep research producing a fully written, source-validated literature review on an agricultural question, as a senior agricultural scientist of the relevant discipline: scope, design the method, discover and screen by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review through an editorial and integrity loop. Same 12-subagent machinery as food-deep-research, grounded in agriculture and multidisciplinary literature (Q1/Q2 preferred, Q4 avoided). Use standalone for an agricultural deep dive, or as the engine called by agri-research. Triggers: deep research agriculture, investigate this agronomy question, agricultural literature review, state of the evidence in soil science, deep dive crop research.

Tous les Skills associés

Parcourez l’association complète par popularité du dépôt ou activité récente de la source.

Les noms et descriptions des Skills restent dans la langue fournie par leur dépôt source.

Trier par
agri-deep-research
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Deep research producing a fully written, source-validated literature review on an agricultural question, as a senior agricultural scientist of the relevant discipline: scope, design the method, discover and screen by journal ranking, validate every source, extract and verify evidence, synthesize, stress-test, then write and format the review through an editorial and integrity loop. Same 12-subagent machinery as food-deep-research, grounded in agriculture and multidisciplinary literature (Q1/Q2 preferred, Q4 avoided). Use standalone for an agricultural deep dive, or as the engine called by agri-research. Triggers: deep research agriculture, investigate this agronomy question, agricultural literature review, state of the evidence in soil science, deep dive crop research.
agri-paper
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Multi-subagent manuscript system for agricultural science, written as a senior agricultural scientist of the relevant discipline: understand the field, frame questions, curate data, run statistics, build figures and tables, construct the discussion, draft, polish, and self-review — journal-aware throughout. Same machinery as food-paper, grounded in agriculture literature (Q1/Q2 preferred, Q4 avoided) and agricultural reporting standards for field trials, animal work and soils. Includes a format-convert mode that reformats a finished manuscript for another journal without touching the science. Triggers: write my agronomy paper, draft an agricultural manuscript, soil science paper, horticulture paper, animal science manuscript, analyze my field trial and write it up, format for an agriculture journal, reformat my manuscript for a different journal, my agricultural paper is finished I just need the formatting.
agri-pipeline
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Master orchestrator for the whole agricultural research-to-publication workflow, run as a senior agricultural scientist. Coordinates the agri skills — journal selection, research (agri-research or agri-deep-research), writing and analysis (agri-paper), figures (food-figure), peer review (agri-review), revision and finalization — into one governed path with quality gates. Same machinery as food-pipeline, grounded in agriculture and multidisciplinary literature (Q1/Q2 preferred, Q4 avoided). Use when the user wants the entire agricultural process managed end to end. Triggers: run the full agricultural paper workflow, take my field trial from research to submission, manage my whole agronomy project, agricultural research to publication, end-to-end agriculture paper.
agri-research
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Run a comprehensive, multi-source literature and evidence-synthesis workflow for agricultural science, as a senior agricultural scientist of the relevant discipline (agronomy, soil science, horticulture, dairy and animal science, agricultural engineering, or agricultural economics). Same machinery as food-research, but the evidence base is agriculture and multidisciplinary literature ranked by journal quartile: Q1/Q2 agriculture journals plus the Nature, Science, Cell and PNAS families first, Q3 only for gaps, Q4 avoided. Use to research an agricultural topic in depth, do a literature review, build an evidence brief, or scope a systematic review. Triggers: research this agricultural topic, agronomy literature review, soil science evidence synthesis, horticulture review, animal science evidence, crop research, farming systems review, what does the agricultural evidence say.
agri-review
28
PangenomeAIPangenomeAI/academic-skills-food-nutrition
Multi-reviewer peer-review system for agricultural manuscripts. Simulates an editorial panel — a coordinating editor, three domain reviewers (methodology, domain/novelty, integrity/ethics) and a devil's advocate — plus a formatting check against the target journal, all acting as senior agricultural scientists. Same machinery as food-review, including the knowledge_builder that reads the cited sources and key field literature first, grounded in agriculture literature (Q1/Q2 preferred, Q4 avoided) and agricultural standards for field trials, experimental unit and pseudoreplication, animal ethics and soils. Triggers: review my agronomy paper, peer review agricultural manuscript, referee report soil science, critique my crop paper, pre-submission review agriculture, mock review animal science.
capri-environmental
16
chrispahmchrispahm/gams-ide
Reference guide for CAPRI environmental indicators and emissions modeling. Use this skill when the user asks about GHG emissions, greenhouse gas, nutrient balances, NPK, nitrogen, phosphorus, potassium, energy use in agriculture, environmental indicators, IPCC methodology, manure management, fertilizer allocation, ammonia emissions, emission factors, carbon cycle, carbon balance, nitrate leaching, soil erosion, N2O, CH4, CO2 from agriculture, enteric fermentation, manure storage, manure application, over-fertilization, nutrient availability, atmospheric deposition, biological fixation, crop residues, emission intensity, tradable GHG permits, livestock density limits, nitrates directive, NEC directive, mitigation technologies, anaerobic digestion, feed additives, precision farming, or CAPDIS nitrogen disaggregation. Also trigger when exploring environmental data in CAPRI GDX files or writing scenario code that involves environmental constraints.

12 Skills sont maintenant affichés.