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Record W2381678631

Discussion on Measures of Prevention and Control of the Four Pests by Planned Construction of Residential Quarter of Shalco

2003· article· en· W2381678631 on OpenAlexaboutno aff
Liu Shan-zhe

Bibliographic record

VenueZhongguo meijie shengwuxue ji kongzhi zazhi · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)CockroachClearingToxicologyEnvironmental scienceEnvironmental protectionEcologyGeographyBusinessBiology
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate the four pests (rat,mosquito,housefly and cockroach) ecologic environment by planned construction of residential quarter of Shalco.Methods To compare the pros and cons of four pests' ecologic environment by planned construction of residential quarter.Results The four pests' ecologic environment has been at a great deal destroyed due to the following facts:demolishment of 122 sets of single-storey house,blocking 166 passageways of building apartment,setting up markets of agricultural products and foodstuff in residential quarter and then clearing away the pedlars at roadsides,dredging ditches,cleaning up street corners and lanes,removing constructional dump in front of the building,etc.The integration of the supplying warm wind,thermal island effect and green house effect brought about a density peak of flies and mosquitoes and cockroach in March and April. Large-scale plantation resulted in the increase in grass land mosquito density.Conclusion The rectifying scheme of destroying four pests' ecologic environment should be put into the designing of the residential quarter.And leaders' attention and every variety of fund is the basic guarantee.The direction of disinfecting and control by chemical drug should be adjusted after the environment change,meanwhile, control of mosquito and housefly and cockroach in winter should also be strengthened especially.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.362

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)0.0000.000

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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