"Flora of the Hudson Bay Lowland and its Postglacial Origins" by John L. Riley. 2003. [book review]
Bibliographic record
Abstract
This computerized guide to 70 fern species of northeastern North America has been loosely based upon Eugene Ogden's Field Guide to Northeastern Ferns, published by the New York State Museum in 1981, one of the earliest publications to employ randomaccess keys in fern identification.According to the introduction to the CD, "this package provides a menu-driven, fully color-illustrated guide and random-access key to ferns of the northeastern United States and eastern Canada.With it, the user may identify a fern by merely matching its characteristics with illustrations on screens provided.This allows a beginner to proceed with the identification of a fern after learning about five simple terms indicated on the help screen.As each feature of the fern in question is chosen, a decreasing number is displayed on the main screen, indicating how many regional fern species share that combination of characters."Unfortunately, the Northeastern Fern Identifier is a DOS-based program.Its approach to interacting with a computer's video card is not compatible with recent operating systems, and it will not function on most computers running Windows NT, 2000, or XP.It will function on older computers running Windows 95 or 98.This is a serious limitation that means the program cannot be used on the vast majority of current computers.I was unable to contact the author by e-mail to determine whether or not a version more compatible with more up to date operating systems is planned.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".