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Effects of Re-Used Plastic Film Mulching on Soil Temperature and Sunflower’s Emergence

2012· article· en· W1999315289 on OpenAlex
Jian Guo Shi, Jing Hui Liu, Bao Ping Zhao, Li Jia, Qin Chen, S. N. Acharya, Ya Fei Yan, Xiao Rong

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced materials research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsAgriculture and Agri-Food Canada
FundersDivision of Materials Research
KeywordsMulchPlastic filmSowingGerminationSunflowerHorticultureMaterials scienceAgronomyBiologyComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

Aiming at reducing agricultural pollution caused by plastic film, the study compared with new plastic film mulching and bare field, to investigating the effects of re-used plastic film mulching on soil temperatures, seed emergence and all seedlings period were studied in Hetao area, China. The results showed that, (1) compared with bare field, the soil temperature of re-used film mulching increased 1.3~4.0 °C and 0.7~1.8 °C separately in the highest and lowest temperature stage. The soil average temperature of upper soil layer (0~20 cm) increased 1.7~2.1°C, and 1.3~2.0 °C lower than new film mulching. (2) Compared with bare field, Daily maximum and minimum temperatures of re-used film mulching were postponed about 1 hour, similar as new film mulching. (3) During emergence stage (7 days after sowing), accumulated temperature of re-used film mulching was 21.6°Cand 23.8 °C higher than that of bare field in depth of 5 cm and 10 cm. Compared with new film mulching, it was 12.4 °Cand 10.0 °C lower in depth of 5 cm and 10 cm. (4) Mulching with re-used film could effectively shorten seed germination for 1-2 days and shorten all seedlings period for 2-3 days compared with bare field, and no difference with new film mulching.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.288
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it