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Record W2113971166 · doi:10.1016/j.jala.2009.07.004

LINA: A Laboratory Inventory System for Oligonucleotides, Microbial Strains, and Cell Lines

2010· article· en· W2113971166 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJALA Journal of the Association for Laboratory Automation · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsIdentifierComputer scienceTable (database)DatabaseRelational databaseIdentification (biology)SoftwareWorld Wide WebInformation retrievalOperating systemBiologyProgramming language

Abstract

fetched live from OpenAlex

In this article, we present the Laboratory Inventory Network Application (LINA), a software system that assists research laboratories in keeping track of their collections of biologically relevant materials. This open source application uses relational Microsoft Access database technology as a back end and a Microsoft .NET application as a front end. Preconstructed table templates are provided that contain standardized and customizable data fields. As new samples are added to the inventory, each is provided with a unique laboratory identifier, which is assigned automatically and sequentially, allowing rapid retrieval when a given reagent is required. The LINA contains a number of useful search tools including a general search, which allows database searches using up to four user-defined criteria. The LINA represents an easily implemented and useful organizational tool for biological laboratories with large numbers of strains, clones, or other reagents.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.295
Teacher spread0.273 · 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