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Record W2048955821 · doi:10.4161/psb.21661

Tuning of color contrast signals to visual sensitivity maxima of tree shrews by three Bornean highland Nepenthes species

2012· article· en· W2048955821 on OpenAlexaff
Jonathan A. Moran, Charles Clarke, Melinda Greenwood, Lijin Chin

Bibliographic record

VenuePlant Signaling & Behavior · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsBiologyContrast (vision)Tree (set theory)BotanySensitivity (control systems)Color contrastZoologyArtificial intelligenceMathematicsCombinatorics

Abstract

fetched live from OpenAlex

Three species of Nepenthes pitcher plants (Nepenthes rajah, Nepenthes lowii and Nepenthes macrophylla) specialize in harvesting nutrients from tree shrew excreta in their pitchers. In all three species, nectaries on the underside of the pitcher lid are the focus of the tree shrews' attention. Tree shrews are dichromats, with visual sensitivity in the blue and green wavebands. All three Nepenthes species were shown to produce visual signals, in which the underside of the pitcher lid (the area of highest nectar production) stood out in high contrast to the adjacent area on the pitcher (i.e., was brighter), in the blue and green wavebands visible to the tree shrews. N. rajah showed the tightest degree of "tuning," notably in the green waveband. Conversely, pitchers of Nepenthes burbidgeae, a typical insectivorous species sympatric with N. rajah, did not produce a color pattern tuned to tree shrew sensitivity maxima.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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

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 head0.034
GPT teacher head0.233
Teacher spread0.199 · 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 designBench or experimental
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

Citations19
Published2012
Admission routes1
Has abstractyes

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