Species differentiation of North American spruce (<i>Picea</i>) based on morphological and anatomical characteristics of needles
Bibliographic record
Abstract
Differentiation of most North American spruce (Picea) species can be done based on needle morphology and anatomy. Picea breweriana S. Watson, Picea chihuahuana Martìnez, Picea mariana (Mill.) BSP, Picea martinezii Patterson, and Picea rubens Sarg. needles have two continuous resin ducts extending from near the base to near the tip. Picea engelmannii Parry ex Engelm., Picea glauca (Moench) Voss, Picea pungens Engelm., Picea mexicana Martìnez, and Picea sitchensis (Bong.) Carr. needles have variable numbers of short, intermittent resin ducts or sacs. Within each of these groups, most species could be differentiated based on cross-sectional shape, resin-duct diameter, and resin-duct position. Picea mariana and P. rubens, and P. glauca and P. engelmannii are two pairs with similar needles, but they can be differentiated using linear discriminant analysis based on resin-duct diameter and position in cross section. Paleoecological and paleoclimatological studies may be facilitated by species-level identification of plant macrofossils because of different ecological adaptations of each species. Resin-duct continuity patterns are generally consistent with current taxonomic classifications, except for P. glauca. Based on our results, together with DNA and crossing studies, P. glauca is apparently more closely related to P. engelmannii and P. sitchensis than to P. rubens and P. mariana, with which it is often classified. Picea pungens is probably more distantly related to P. engelmannii than has been assumed in some previous classifications. Picea martinezii and P. chihuahuana may be very closely related to each other.Key words: spruce, Picea, North America, needle, resin duct, anatomy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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 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".