Analysis of the Interaction Between Timber Markets and the Forest Resources of Maine
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.
Bibliographic record
Abstract
Abstract The abundant timber resources of Maine are critical to the State's timber economy; thus, when the 1995 forest inventory indicated a 20% decline in softwood growing stock, there was great concern by industry and government. Furthermore, declining near-term softwood growing stock levels were forecast. To better understand what was occurring in Maine's forest, we examined changes in composition and evaluated the relative impacts of harvesting versus growth and mortality. Much of the decline in spruce-fir inventory can be attributed to the budworm infestation of the 1970s and 1980s, although continued high utilization contributed to the decline. The high rate of softwood utilization was facilitated by low softwood timber prices due to increased supply from salvage cutting and high prices for softwood dimension lumber. The high price of dimension lumber also allowed the adoption of sawmill technology in Canada and Maine that used small-diameter logs, formerly consumed by the pulp industry, for lumber production. The increased demand for spruce-fir roundwood occurred during a period when changes in paper demand and pulping technology increased the demand for hardwood pulpwood. Unlike spruce-fir and hemlock, hardwood growing-stock volumes have increased steadily due to low utilization, high growth, and low mortality. Ample inventories of hardwoods have allowed increased volumes of these species to be used in the manufacture of pulp and engineered wood products. A recent partial forest survey of Maine indicated that spruce-fir growing stock inventory has stabilized as a result of regeneration of these species that began after the last spruce budworm infestation. North. J. Appl. For. 21(3):135–143.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it