# Methods in Ecology and Evolution (@MethodsEcolEvol) on x

- id: koinon:creator:x_methodsecolevol
- url: https://koinonlink.com/kol/x/MethodsEcolEvol
- schema_version: 1.4

## Identity
- platform: x
- handle: MethodsEcolEvol
- platform_url: https://twitter.com/MethodsEcolEvol
- website: https://besjournals.onlinelibrary.wiley.com/journal/2041210x
- country: United Kingdom
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 27247
- following: 7959
- posts_total: 10385
- posts_observed: 10
- posts_per_day: 1.676
- account_age_days: 6195
- verified: false
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00033
- best_post_interactions: 9
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: entertainment
- subcategory: edu_science
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: Ecological genetics special features, Webinars on statistical methods, Journal issue highlights and covers, Classification algorithms and barcode methods
- bio: MEE is a scientific journal promoting new methods in #ecology & #evolution, and facilitating their dissemination and uptake by the #research community.

## Audience (inferred)
- status: present
- description: Ecology and evolution researchers, mainly academic scientists, postdocs and PhD students who develop or apply new methods
- roles: data
- seniority: practitioner
- pain_points: Finding and validating new statistical or computational methods for field data, Publishing methodological advances in high-impact journals, Keeping up with cross-disciplinary tools like classification algorithms or state-space models, Accessing webinars and special features on emerging techniques
- posts_analysed: 4
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.4
- promotion_intent: 0.2
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 35
- authenticity_basis: engagement_observed
- credibility_score: 70
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_methodsecolevol#67ffae06] MEE is collaborating on this Ecological Genetics cross-journal special feature. See below for more information and to submit your proposal! (https://twitter.com/MethodsEcolEvol/status/2056692005942481390)
- [x_methodsecolevol#34157114] Missed out latest MEE live? Head over to our Youtube! In this webinar, author Quinn Asena introduces multinomialTS, a state-space method for estimating coefficients of biotic interactions and driver-species relationships from community time series. https://t.co/sl1WfaAmIE
- [x_methodsecolevol#f46fabd7] Our July Issue is now out! 🚨 This months cover shows Grévy's zebras grazing beneath gathering clouds at Mpala, Kenya, during an evening drone mission conducted in 2022 as part of the WildCap project 🦓 Find out more and read the whole issue here 👇 https://t.co/4xyCApFCb5 https:
- [x_methodsecolevol#fc2d1222] 📖 Published📖 This study sheds light on the strengths and limitations of different classification algorithms across taxonomic groups and barcode characteristics🧬 🍄 🧪 https://t.c

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=66, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=66, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=66, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=77, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=77, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=108, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=77, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=108, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 77
- audience_updated_days_ago: 66

## AI retrieval
- indexing_requests: 10
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_methodsecolevol
- Request removal: https://koinonlink.com/claim?k=x_methodsecolevol
- Terms: https://koinonlink.com/for-ai