PBS software: maps, spatial analysis, and other utilities
Bibliographic record
Abstract
Schnute, J.T., N.M. Boers, and R. Haigh. 2003. PBS software: maps, spatial analysis, and other utilities. Can. Tech. Rep. Fish. Aquat. Sci. 2496: viii + 82 p. This report describes software written to facilitate the compilation and analysis of fishery data, particularly data referenced by spatial coordinates. Our research stems from experiences with information on Canadas Pacific groundfish fisheries compiled at the Pacific Biological Station (PBS). Despite its origins in fishery data analysis, our software has broad applicability. The library PBS Mapping extends the languages R and S-PLUS to include two-dimensional plotting features similar to those commonly available in a Geographic Information System (GIS). Embedded C code speeds algorithms from computational geometry, such as finding polygons that contain specified point events or converting between longitude-latitude and Universal Transverse Mercator (UTM) coordinates. We also present a number of convenient utilities for the Microsoft Windows operating systems, including commands that support computational geometry outside the framework of R or S-PLUS. Tools to construct most of our software come freely from the Internet, as documented here in a guide to the packages available. Furthermore, we provide quick tutorials that address key technical issues relevant to our work, such as embedding C code into an R package and writing documentation that meets the R standard. Our results, which depend significantly on the work of students, illustrate the convergence of goals between academic training and applied research. RESUME Schnute, J.T., N.M. Boers, and R. Haigh. 2003. PBS software: maps, spatial analysis, and other utilities. Can. Tech. Rep. Fish. Aquat. Sci. 2496: viii + 82 p. Ce rapport presente un logiciel concu pour faciliter la compilation et lanalyse de donnees sur la peche, particulierement de donnees georeferencees. Notre recherche decoule de notre experience de la compilation de donnees sur la peche du poisson de fond dans le Pacifique a la Station biologique du Pacifique (SBP). Bien quil ait ete concu pour analyser des donnees sur la peche, notre logiciel est dapplication tres generale. La cartotheque logicielle PBS Mapping permet de developper les langages R et S-PLUS afin quils comprennent des capacites de tracage bidimensionnel semblables a celles disponibles couramment dans un systeme dinformation geographique (SIG). Le langage C permet daccelerer les algorithmes geometriques, comme ceux qui permettent de rechercher des polygones comportant des evenements ponctuels precis ou de convertir des coordonnees geographiques en coordonnees de Mercator transverse universelle. Nous presentons egalement un certain nombre dapplications pratiques pour les systemes dexploitation Windows de Microsoft, y compris des commandes de geometrie algorithmique a lexterieur du cadre des langages R et S-PLUS. Les outils utilises pour mettre au point la plupart de nos logiciels sont disponibles gratuitement sur Internet, tel que souligne dans un guide des progiciels disponibles presente dans ce document. De plus, nous offrons de courts didacticiels qui traitent des principales questions techniques liees a notre travail, comme lintegration de code C dans un progiciel en langage R et la redaction de documents qui satisfont a la norme du langage R. Nos resultats, qui dependent grandement du travail detudiants, illustrent la convergence des objectifs de la formation academique et de la recherche appliquee.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.281 | 0.294 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".