Demands on Lumber Suppliers within the US Prodealers Channel
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
Prodealers are building materials suppliers whose client base comes mostly from the homebuilding industry. Because they represent an important channel for wood products, a 2007 survey of US prodealers examined (1) lumber attributes demanded, (2) products and suppliers requirements, (3) trends in substitution between countries supplying lumber to the United States, and (4) trends toward prefabrication of structural components. Forty-six prodealers were surveyed; most answered for multiple stores. On average, respondents purchased 60 million board feet of lumber in 2007, and their overall consumption was estimated at 2.76 billion board feet. By far, the most common grade in the prodealer segment is dimension lumber (No. 2 and Better), and the most common type is the spruce-pine-fir species group (SPF). Within the sample, 5 percent of US lumber imports came from offshore. Canada supplied 51 percent of the lumber purchased by respondents, and the United States supplied 47 percent. Wane as well as warp and twist were consistently identified as the most challenging lumber attributes for prodealers. Product quality was identified as a primary reason for changing lumber suppliers. In characterizing properties of the dimension lumber imported from Europe to the United States, it was found that European lumber stands out mostly for visual appearance and low wane. For customer support and timely deliveries, respondents tended to favor US mills. The study suggests that customers are not fully satisfied with lumber, especially with regard to wane and straightness, and that lumber quality issues may be more important today than in the past.
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 | 0.001 | 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 | 0.001 | 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) | 0.001 | 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 it