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Record W4403232943 · doi:10.15560/20.5.1096

An annotated checklist of the lichen biodiversity at two Mars analog sites: The Mars Desert Research Station (Utah, USA) and The Flashline Mars Arctic Research Station (Nunavut, Canada) recorded during the Mars 160 Mission

2024· article· en· W4403232943 on OpenAlexfundaboutno aff
Paul C. Sokoloff, A. Srivastava, R. Troy McMullin, Jonathan Clarke, J. P. Knightly, Anastasia Stepanova, Alexandre Mangeot, Claude-Michel Laroche, Annalea Beattie, Shannon Rupert

Bibliographic record

VenueCheck List · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersCanadian Museum of Nature
KeywordsMars Exploration ProgramExploration of MarsMars landingArcticChecklistLichenEnvironmental scienceGeographyAstrobiologyRemote sensingGeologyEcologyOceanographyBiology

Abstract

fetched live from OpenAlex

During the Mars 160 Mission in 2016 and 2017, crews at the Mars Desert Research Station (MDRS) in Utah, USA and the Flashline Mars Arctic Research Station (FMARS) on Tallurutit (Devon Island), Nunavut, Canada, conducted a collections‑based survey of lichen biodiversity at each of these Martian planetary analogs. Here we present the results of these studies as two annotated checklists, including 35 lichen spe‑ cies from MDRS and 13 species from FMARS, alongside details on the distribution of these species, relevant taxonomic notes, and photos of each species as an identification aid. This work adds to our knowledge of the biodiversity of these unique sites and provides an important baseline for future analog research at these stations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.007
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.002

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.

Opus teacher head0.052
GPT teacher head0.322
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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