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Record W6894137983 · doi:10.5281/zenodo.7819394

Achnanthidium minutissimum Czarn. (Czarnecki 1994

2022· article· en· W6894137983 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsCanadian Museum of Nature
Fundersnot available
KeywordsTaperingMargin (machine learning)ExpansiveRegular polygonSubaerial

Abstract

fetched live from OpenAlex

Achnanthidium minutissimum (Kütz.) Czarn. (Fig. 14) Memoirs of the California Academy of Sciences 17: 157 (Czarnecki 1994). — Basionym: Achnanthes minutissima Kütz., Linnaea 8 (5): 578, pl. 16, fig. 54 (Kützing 1833); Kützing, 50, pl. 4, fig. 54 (Kützing 1834); Kützing, Dec. VIII, no. 75 (Kützing 1834), in Kützing, Algarum Aquae Dulcis Germanicum, Decades I-XVI, numbers 1-160. Halis Saxonum, 1833-1836. DESCRIPTION LM (Fig. 14 A-AW) Frustules slightly arched, with convex RL, concave RV. Valves linear-lanceolate. Margins tapering gradually towards short protracted rounded, rostrate poles. Valve dimensions (n = 46): length 8.5-15 µm, width 2.5-3.5 µm. Central area on raphe valve varies from small rounded to a narrow rectangular fascia on one or both sides. Striae more widely spaced in valve centre. Raphe filiform, straight, central pores slightly widened, terminating close to margin of central area. Central area on rapheless valve indistinct or narrow elliptical. Axial area narrow linear on both valves, slightly widening towards valve centre. Striae radiate throughout on both valves, 30-35 in 10 µm (RV and RL), becoming denser at poles.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.033
GPT teacher head0.253
Teacher spread0.220 · 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
Published2022
Admission routes1
Has abstractyes

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