Bibliographic record
Abstract
Agromyza ambrosivora Spencer (Fig. 64) Material examined. COLORADO: Chaffee Co., Poncha Springs, South Arkansas River, 8.vii.2015, em. 28.vii– 1.viii.2015, C.S. Eiseman, ex Helianthus annuus, #CSE1872, CNC654328–654332 (1♂ 4♀); MASSACHUSETTS: Worcester Co., Sturbridge, Leadmine Rd., 6.vii.2013, em. 20.vii.2013, C.S. Eiseman, ex Ambrosia artemisiifolia, #CSE725, CNC392679, CNC392680 (2♀); PENNSYLVANIA: Chester Co., Pottstown, Warwick County Park, 10.viii.2014, em. 2.ix.2014, N. D. Charney, ex Ambrosia trifida, #CSE1371, CNC384846 (1♂). Hosts. Asteraceae: Ambrosia artemisiifolia L., A. * trifida L., * Helianthus annuus L. Some specimens from Los Angeles and Ventura Counties, California, were caught at sites where Artemisia douglasiana Besser was one of the dominant plants, and Spencer (1981) stated that it therefore seems probable that this was the host. He noted that Ambrosia is not known in these counties, but the genus is now known from both counties and several Helianthus species are also present (USDA, NRCS 2017). Leaf mine. (Fig. 64) On Ambrosia artemisiifolia, “several larvae frequently feeding together to form a blackish leaf-mine, which extends from the apex of the pinnately divided leaves towards the midrib” (Spencer 1969). In our example the apices of three lobes were disfigured by the mine. The mine on A. trifida was a brown blotch in the angle between the midrib and a lateral vein; there was a narrow initial linear portion that had been mostly obliterated. The mines on Helianthus (Fig. 64) began near the leaf margin in the basal half of the leaf blade and followed the margin apically, widening gradually. Puparium. Brown; formed outside the mine. Distribution. USA: CA, *CO, *MA, MD (Scheffer et al. 2007), NY (Scheffer & Lonsdale 2018), *PA; Canada: ON.
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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 | 0.001 | 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) | 0.006 | 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".